Analysis of Mutual Fund Performance

#PROJECT-4: Mutual Fund(Indian) Performance based on Five Key Indicators

knitr::opts_chunk$set(root.dir = "C:/Users/rsman/Documents/PERS FOLDERS/RAJDEEP/INVESTMENTS/ANALYSIS/DATA")

library(lubridate)
library(stringr)
library(pander)
library(data.table)
library(xlsx)
library(dplyr)
library(scales)
library(ggplot2)
library(Quandl)
library(tabulizer)
library(knitr)
library(kableExtra)
library(formattable)
library(DT)
library(rio)

knitr::opts_chunk$set(echo = TRUE)
knitr::opts_chunk$set(root.dir = "C:/Users/rsman/Documents/PERS FOLDERS/RAJDEEP/INVESTMENTS/ANALYSIS/DATA")
getwd()

[1] “C:/Users/rsman/Documents/PERS FOLDERS/RAJDEEP/INVESTMENTS/ANALYSIS/DATA”

###Functions
colFmt1 = function(x,color){
  outputFormat = knitr::opts_knit$get("rmarkdown.pandoc.to")
  if(outputFormat == 'latex')
    paste("\\textcolor{",color,"}{",x,"}",sep="")
  else if(outputFormat == 'html')
    paste("<font color='",color,"'>",x,"</font>",sep="")
  else
    x
}

colFmt = function(x,color){
  outputFormat = knitr::opts_knit$get("rmarkdown.pandoc.to")
  if(outputFormat == 'html')
    paste("<font color='",color,"'>",x,"</font>",sep="")
  else
    x
}

makeCharac <- function(rx.vr){
  new.vr <- as.character(rx.vr)
  return(new.vr)
}

makeNumeric <- function(rx.vr){
  new.vr <- as.numeric(rx.vr)
  return(new.vr)
}


###End Functions

CWD <- "C:/Users/rsman/Documents/PERS FOLDERS/RAJDEEP/INVESTMENTS/ANALYSIS/DATA/"
setwd("C:/Users/rsman/Documents/PERS FOLDERS/RAJDEEP/INVESTMENTS/ANALYSIS/DATA")
CWD <- getwd()

knitr::opts_chunk$set(echo = TRUE)
pandoc.header(colFmt("Section-1: MF Performance using Valuresearchonline Data", 'red'), 1, 'setext')

Section-1: MF Performance using Valuresearchonline Data

data.org <- function(rx.df){
  rx.df <- rx.df[-1:-5,]
  for (ctr in 1: ncol(rx.df)) {
    rx.df[,ctr]<- makeCharac(rx.df[,ctr])
    }
  
  colnames(rx.df) <- rx.df[1,]
  rx.df <- rx.df[-1,]
  return(rx.df)
  
}

vr.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_snapshot.csv"), header = FALSE))
vr_x.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_snapshot_1.csv"), header = FALSE))
vr_y.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_snapshot_2.csv"), header = FALSE))
vr.df <- rbind(vr.df, vr_x.df, vr_y.df)
vr.df <- data.org(vr.df)

vr2.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_returns.csv"), header = FALSE))
vr2.df <- data.org(vr2.df)
vr2_lt.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_returns_lt.csv"), header = FALSE))
vr2_lt.df <- data.org(vr2_lt.df)
vr2.df <- merge(vr2.df, vr2_lt.df, by.x = "Fund Name", by.y = "Fund Name")

vr2_x.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_returns_1.csv"), header = FALSE))
vr2_x.df <- data.org(vr2_x.df)
vr2_x_lt.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_returns_1_lt.csv"), header = FALSE))
vr2_x_lt.df <- data.org(vr2_x_lt.df)
vr2_x.df <- merge(vr2_x.df, vr2_x_lt.df, by.x = "Fund Name", by.y = "Fund Name")


vr2_y.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_returns_2.csv"), header = FALSE))
vr2_y.df <- data.org(vr2_y.df)
vr2_y_lt.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_returns_2_lt.csv"), header = FALSE))
vr2_y_lt.df <- data.org(vr2_y_lt.df)
vr2_y.df <- merge(vr2_y.df, vr2_y_lt.df, by.x = "Fund Name", by.y = "Fund Name")

vr2.df <- rbind(vr2.df, vr2_x.df, vr2_y.df)

vr3.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_risk.csv"), header = FALSE))
vr3_x.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_risk_1.csv"), header = FALSE))
vr3_y.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_risk_2.csv"), header = FALSE))
vr3.df <- rbind(vr3.df, vr3_x.df, vr3_y.df)
vr3.df <- data.org(vr3.df)

vr4.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_portfolio.csv"), header = FALSE))
vr4_x.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_portfolio_1.csv"), header = FALSE))
vr4_y.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_portfolio_2.csv"), header = FALSE))
vr4.df <- rbind(vr4.df, vr4_x.df, vr4_y.df)
vr4.df <- data.org(vr4.df)

vr5.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_nav.csv"), header = FALSE))
vr5_x.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_nav_1.csv"), header = FALSE))
vr5_y.df <- as.data.frame(read.csv(paste0(CWD,"/PERFORMANCE/vr_nav_2.csv"), header = FALSE))
vr5.df <- rbind(vr5.df, vr5_x.df, vr5_y.df)

analysis.df <- as.data.frame(read.xlsx(paste0(CWD,"/PERFORMANCE/ratio_analysis.xlsx"), sheetIndex = 1, header = TRUE))





vr.df <- merge(vr.df, vr2.df, by.x = "Fund Name", by.y = "Fund Name")
vr.df <- merge(vr.df, vr3.df, by.x = "Fund Name", by.y = "Fund Name")
vr.df <- merge(vr.df, vr4.df, by.x = "Fund Name", by.y = "Fund Name")

rm(vr2.df)
rm(vr3.df)
rm(vr4.df)

r_sq.vr <- as.numeric(as.character(analysis.df[analysis.df$type=="r_sq",2]))
beta.vr <- as.numeric(as.character(analysis.df[analysis.df$type=="beta",2]))
alpha.vr <- as.numeric(as.character(analysis.df[analysis.df$type=="alpha",2]))
sharpe_ratio.vr <- as.numeric(as.character(analysis.df[analysis.df$type=="sharpe_ratio",2]))
expense_ratio.vr <- as.numeric(as.character(analysis.df[analysis.df$type=="expense_ratio",2]))*100
max.values <- c(r_sq.vr, beta.vr, alpha.vr, sharpe_ratio.vr, expense_ratio.vr)

r_sq.min <- as.numeric(as.character(analysis.df[analysis.df$type=="r_sq",3]))
beta.min <- as.numeric(as.character(analysis.df[analysis.df$type=="beta",3]))
alpha.min <- as.numeric(as.character(analysis.df[analysis.df$type=="alpha",3]))
sharpe_ratio.min <- as.numeric(as.character(analysis.df[analysis.df$type=="sharpe_ratio",3]))
expense_ratio.min <- as.numeric(as.character(analysis.df[analysis.df$type=="expense_ratio",3]))*100
min.values <- c(r_sq.min, beta.min, alpha.min, sharpe_ratio.min, expense_ratio.min)

########

aa.mf <- vr.df

aa.mf$`R-Squared` <- makeNumeric(aa.mf$`R-Squared`)
aa.mf$Beta <- makeNumeric(aa.mf$Beta)
aa.mf$Alpha <- makeNumeric(aa.mf$Alpha)
aa.mf$`Sharpe Ratio` <- makeNumeric(aa.mf$`Sharpe Ratio`)
aa.mf$`Expense Ratio (%)` <- makeNumeric(aa.mf$`Expense Ratio (%)`)
aa.mf$`1 Yr Ret (%).x` <- makeNumeric(aa.mf$`1 Yr Ret (%).x`)
aa.mf$`3 Yr Ret (%)` <- makeNumeric(aa.mf$`3 Yr Ret (%)`)
aa.mf$`5 Yr Ret (%)` <- makeNumeric(aa.mf$`5 Yr Ret (%)`)
aa.mf$`10 Yr Ret (%)` <- makeNumeric(aa.mf$`10 Yr Ret (%)`)
aa.mf$`Net Assests (Cr).x`<- makeNumeric(aa.mf$`Net Assets (Cr).x`)

#Remove all NA from aa.mf
if (nrow(aa.mf[is.na(aa.mf$`Expense Ratio (%)`),])>0) {
  aa.mf <- aa.mf[-which(is.na(aa.mf$`Expense Ratio (%)`)),]
}

if (nrow(aa.mf[is.na(aa.mf$`R-Squared`),])>0) {
  aa.mf <- aa.mf[-which(is.na(aa.mf$`R-Squared`)),]
}

if (nrow(aa.mf[is.na(aa.mf$`Sharpe Ratio`),])>0) {
  aa.mf <- aa.mf[-which(is.na(aa.mf$`Sharpe Ratio`)),]
}

if (nrow(aa.mf[is.na(aa.mf$Alpha),])>0) {
  aa.mf <- aa.mf[-which(is.na(aa.mf$Alpha)),]
}

if (nrow(aa.mf[is.na(aa.mf$Beta),])>0) {
  aa.mf <- aa.mf[-which(is.na(aa.mf$Beta)),]
}

vr.df.new <- aa.mf
vr.df.new$Launch <- gsub(",","",vr.df.new$Launch)
vr.df.new$Launch <- gsub(" ","/",vr.df.new$Launch)
#vr.df.new$Launch <- as.Date(vr.df.new$Launch, "%m/%d/%Y")
vr.df.new$Launch <- mdy(vr.df.new$Launch)


#aa.mf <- vr.df
aa.mf$rank1 <- as.numeric(substr(aa.mf$`1 Yr Rank.x`,1,unlist(str_locate(aa.mf$`1 Yr Rank.x`,"/"))[,1]-1))
aa.mf <- aa.mf[-which(is.na(aa.mf$rank1)),]
selected.mf <- aa.mf[aa.mf$rank1 <=10,]
selected.mf <- aa.mf

r_sq.avg <- mean(selected.mf$`R-Squared`)
beta.avg <- mean(selected.mf$Beta)
alpha.avg <- mean(selected.mf$Alpha)
sharpe_ratio.avg <- mean(selected.mf$`Sharpe Ratio`)
expense_ratio.avg <- mean(selected.mf$`Expense Ratio (%)`)
avg.values <- c(r_sq.avg, beta.avg, alpha.avg, sharpe_ratio.avg, expense_ratio.avg)
tmp.df <- data.frame(matrix(ncol =1, nrow =0))
tmp.df <- rbind(tmp.df, r_sq.avg, beta.avg, alpha.avg, sharpe_ratio.avg, expense_ratio.avg)
colnames(tmp.df) <- c("avg")
analysis.df <- cbind(analysis.df, tmp.df)

##### old loc


mf.filter <- function(mf.rx, values.rx ){
  
  rsq.rx<- values.rx[1]
  beta.rx <- values.rx[2] 
  alpha.rx <- values.rx[3]
  shrpe.rx <- values.rx[4]
  exp.rx <- values.rx[5]
  
  mf.rx <- mf.rx[mf.rx$`R-Squared`>=rsq.rx,]
  mf.rx <- mf.rx[mf.rx$Beta >= beta.rx,]
  mf.rx <- mf.rx[mf.rx$Alpha>= alpha.rx,]
  mf.rx <- mf.rx[mf.rx$`Sharpe Ratio`>= shrpe.rx,]
  mf.rx <- mf.rx[mf.rx$`Expense Ratio (%)`<= exp.rx,]
  
  return(mf.rx)
  
}

pandoc.header(colFmt("1A: MF's filtered on optimal values of R-Sq, Alpha, Beta, Sharpe Ratio & Exp-Ratio", 'blue'), 1, 'setext')

1A: MF’s filtered on optimal values of R-Sq, Alpha, Beta, Sharpe Ratio & Exp-Ratio

#knitr::kable(analysis.df, caption = colFmt("Filter Values", "blue"))

##$$$$$
paste(colFmt( "Rations/Values used to Compare Mutual Funds (Average Value is based on Present Market Status", "blue"))

[1] “Rations/Values used to Compare Mutual Funds (Average Value is based on Present Market Status”

analysis.df[1:5, 1:4] %>%
  mutate(
    Ser.No = row.names(.),
    Factor = (type),
    Max.Value = (value),
    Min.Value = (min),
    Average.Value =(avg)
  ) %>%
  select(Ser.No,Factor, Max.Value, Min.Value, Average.Value) %>%
  kable(escape = F) %>%
  kable_styling("hover", full_width = F) %>%
  column_spec(5, width = "3cm")

Ser.No	Factor	Max.Value	Min.Value	Average.Value
1	r_sq	0.750	0.600	0.6751398
2	beta	1.100	1.000	0.7643808
3	alpha	2.000	1.400	-0.4640346
4	sharpe_ratio	1.500	0.750	0.4383688
5	expense_ratio	0.015	0.025	1.2104860

##$$$$$


##Filter with max values
top.mf<- mf.filter(aa.mf, max.values)
rownames(top.mf) <- NULL
row.ctr <- nrow(top.mf)
paste(colFmt( "Mutual Funds Meeting the Maximum Criteria", "blue"))

[1] “Mutual Funds Meeting the Maximum Criteria”

top.mf[1:row.ctr,c(1,37,35,36,33,6,7,22)] %>%
  mutate(
    Ser.No = row.names(.),
    Fund = (`Fund Name`),
    R_Sq = (`R-Squared`),
    Beta = (Beta),
    Alpha = (Alpha),
    Sharpe_Ratio = (`Sharpe Ratio`),
    Exp_Ratio = (`Expense Ratio (%)`),
    Return_1Yr =(`1 Yr Ret (%).x`),
    Return_5Yr =(`5 Yr Ret (%)`),
    
  ) %>%
  select(Ser.No,Fund, R_Sq, Beta, Alpha, Sharpe_Ratio, Exp_Ratio, Return_1Yr, Return_5Yr) %>%
  kable(escape = F) %>%
  kable_styling("hover", full_width = F)

Ser.No	Fund	R_Sq	Beta	Alpha	Sharpe_Ratio	Exp_Ratio	Return_1Yr	Return_5Yr
NA	NA	NA	NA	NA	NA	NA	NA	NA

##filter with min values
top.mf<- mf.filter(aa.mf, min.values)
rownames(top.mf) <- NULL
row.ctr <- nrow(top.mf)
paste(colFmt( "Mutual Funds Meeting the Minimum Criteria", "blue"))

[1] “Mutual Funds Meeting the Minimum Criteria”

top.mf[1:row.ctr,c(1,37,35,36,33,6,7,22)] %>%
  mutate(
    Ser.No = row.names(.),
    Fund = (`Fund Name`),
    R_Sq = (`R-Squared`),
    Beta = (Beta),
    Alpha = (Alpha),
    Sharpe_Ratio = (`Sharpe Ratio`),
    Exp_Ratio = (`Expense Ratio (%)`),
    Return_1Yr =(`1 Yr Ret (%).x`),
    Return_5Yr =(`5 Yr Ret (%)`),
    
  ) %>%
  select(Ser.No,Fund, R_Sq, Beta, Alpha, Sharpe_Ratio, Exp_Ratio, Return_1Yr, Return_5Yr) %>%
  kable(escape = F) %>%
  kable_styling("hover", full_width = T)

Ser.No	Fund	R_Sq	Beta	Alpha	Sharpe_Ratio	Exp_Ratio	Return_1Yr	Return_5Yr
1	Axis Dynamic Bond Fund	0.67	1.34	1.71	1.20	0.67	13.29	8.98
2	Axis Dynamic Bond Fund - Direct Plan	0.68	1.33	2.42	1.42	0.25	13.78	9.85
3	ICICI Prudential All Seasons Bond Fund	0.68	1.08	1.58	1.28	1.52	12.66	9.59
4	ICICI Prudential All Seasons Bond Fund - Direct Plan	0.68	1.08	2.28	1.54	0.80	13.42	10.36
5	ICICI Prudential Bond Fund - Direct Plan	0.61	1.13	1.83	1.27	0.56	12.46	9.14
6	IDFC Dynamic Bond Fund - Direct Plan	0.84	1.77	1.61	1.17	0.86	13.89	9.95
7	Kotak Dynamic Bond Fund - Direct Plan	0.67	1.14	2.77	1.64	0.45	12.30	10.31
8	Kotak Dynamic Bond Fund - Regular Plan	0.67	1.14	2.15	1.43	1.15	11.56	9.63
9	L&T Flexi Bond Fund - Direct Plan	0.84	1.38	1.41	1.23	0.96	10.97	9.35
10	L&T Triple Ace Bond Fund	0.71	1.63	1.57	1.11	0.63	13.25	8.59
11	L&T Triple Ace Bond Fund - Direct Plan	0.71	1.63	1.87	1.18	0.29	13.62	9.19
12	Mirae Asset Dynamic Bond Fund - Direct Plan	0.67	1.22	2.11	1.38	0.49	11.40	NA
13	SBI Dynamic Bond Fund - Direct Plan	0.80	1.51	1.61	1.22	0.87	12.01	9.97
14	SBI Magnum Income Fund	0.62	1.12	1.57	1.20	1.47	13.57	9.18
15	SBI Magnum Income Fund - Direct Plan	0.62	1.12	2.31	1.45	0.85	14.26	9.95

##filter wiht average values
top.mf<- mf.filter(aa.mf, avg.values)
rownames(top.mf) <- NULL
paste(colFmt( "Mutual Funds Meeting the Average Criteria", "blue"))

[1] “Mutual Funds Meeting the Average Criteria”

row.ctr <- nrow(top.mf)
top.mf[1:row.ctr,c(1,37,35,36,33,6,7,22)] %>%
  mutate(
    Ser.No = row.names(.),
    Fund = (`Fund Name`),
    R_Sq = (`R-Squared`),
    Beta = (Beta),
    Alpha = (Alpha),
    Sharpe_Ratio = (`Sharpe Ratio`),
    Exp_Ratio = (`Expense Ratio (%)`),
    Return_1Yr =(`1 Yr Ret (%).x`),
    Return_5Yr =(`5 Yr Ret (%)`),
    
  ) %>%
  select(Ser.No,Fund, R_Sq, Beta, Alpha, Sharpe_Ratio, Exp_Ratio, Return_1Yr, Return_5Yr) %>%
  kable(escape = F) %>%
  kable_styling("hover", full_width = T)

Ser.No	Fund	R_Sq	Beta	Alpha	Sharpe_Ratio	Exp_Ratio	Return_1Yr	Return_5Yr
1	Aditya Birla Sun Life Government Securities Fund	0.84	0.77	0.25	0.90	1.18	11.72	9.73
2	Aditya Birla Sun Life Government Securities Fund - Direct Plan	0.84	0.77	0.84	1.03	0.58	12.40	10.33
3	Aditya Birla Sun Life Income Fund	0.78	1.64	0.30	0.83	0.89	12.34	8.39
4	Aditya Birla Sun Life Income Fund - Direct Plan	0.79	1.64	1.00	1.01	0.42	12.94	9.21
5	Axis Dynamic Bond Fund - Direct Plan	0.68	1.33	2.42	1.42	0.25	13.78	9.85
6	BNP Paribas Flexi Debt Fund - Direct Plan	0.80	1.23	0.33	0.88	0.51	10.39	8.53
7	Canara Robeco Dynamic Bond Fund - Direct Plan	0.83	1.43	-0.02	0.77	0.88	10.24	8.59
8	Canara Robeco Income Fund - Direct Plan	0.80	1.37	1.34	1.18	0.75	11.24	9.02
9	DSP Government Securities Fund	0.87	0.79	1.04	1.10	1.07	13.21	9.65
10	DSP Government Securities Fund - Direct Plan	0.88	0.79	1.73	1.27	0.54	13.86	10.31
11	HSBC Flexi Debt Fund - Direct Plan	0.85	1.54	0.06	0.80	0.95	9.43	7.92
12	ICICI Prudential All Seasons Bond Fund - Direct Plan	0.68	1.08	2.28	1.54	0.80	13.42	10.36
13	ICICI Prudential Constant Maturity Gilt Fund	0.87	0.82	2.03	1.31	0.39	13.91	10.60
14	ICICI Prudential Constant Maturity Gilt Fund - Direct Plan	0.87	0.82	2.23	1.36	0.23	14.09	10.84
15	IDFC Bond Fund Medium Term Plan - Direct Plan	0.69	0.95	1.97	1.54	0.76	10.97	8.86
16	IDFC Dynamic Bond Fund - Direct Plan	0.84	1.77	1.61	1.17	0.86	13.89	9.95
17	IDFC Government Securities Fund - Constant Maturity Plan - Direct Plan	0.88	0.80	3.46	1.67	0.48	13.96	11.20
18	IDFC Government Securities Fund - Constant Maturity Plan - Regular Plan	0.88	0.80	3.36	1.65	0.61	13.81	11.06
19	IDFC Government Securities Fund - Investment Plan - Direct Plan	0.90	0.84	1.89	1.30	0.61	14.89	10.55
20	Kotak Asset Allocator Fund - Direct Plan	0.69	1.58	3.05	0.44	0.34	19.23	11.73
21	Kotak Bond Fund - Direct Plan	0.81	1.57	0.97	1.03	0.80	12.66	8.88
22	Kotak Gilt Investment - Direct Plan	0.86	0.82	0.83	1.04	0.45	13.38	9.94
23	Kotak Gilt Investment Provident Fund and Trust Plan - Direct Plan	0.86	0.82	0.83	1.04	0.40	13.38	9.94
24	L&T Flexi Bond Fund - Direct Plan	0.84	1.38	1.41	1.23	0.96	10.97	9.35
25	L&T Triple Ace Bond Fund	0.71	1.63	1.57	1.11	0.63	13.25	8.59
26	L&T Triple Ace Bond Fund - Direct Plan	0.71	1.63	1.87	1.18	0.29	13.62	9.19
27	LIC MF Bond Fund - Direct Plan	0.87	1.45	0.16	0.85	0.18	9.94	7.96
28	Nippon India Dynamic Bond Fund - Direct Plan	0.74	1.64	0.10	0.76	0.25	11.18	8.65
29	Nippon India ETF Long Term Gilt	0.92	0.86	-0.17	0.84	0.10	11.00	NA
30	Nippon India Gilt Securities Fund - Direct Plan	0.93	0.77	1.77	1.32	0.62	12.47	11.11
31	Nippon India Income Fund - Direct Plan	0.86	1.75	1.07	1.06	0.72	11.62	9.44
32	Nippon India Pharma Fund - Direct Plan	0.95	0.85	7.88	0.72	1.16	58.29	10.56
33	Parag Parikh Long Term Equity Fund - Direct Plan	0.85	0.79	7.92	0.44	1.01	27.25	15.13
34	PGIM India Dynamic Bond Fund - Direct Plan	0.84	1.36	1.30	1.20	0.87	10.21	9.70
35	Quantum Dynamic Bond Fund - Direct Plan	0.71	1.08	0.65	0.96	0.63	10.64	8.94
36	Quantum Dynamic Bond Fund - Regular Plan	0.71	1.08	0.54	0.92	0.75	10.49	8.83
37	SBI Dynamic Bond Fund - Direct Plan	0.80	1.51	1.61	1.22	0.87	12.01	9.97
38	SBI Tax Advantage Fund - Series III - Direct Plan	0.82	0.93	10.62	0.49	0.88	29.97	18.04
39	Tata Income Fund - Direct Plan	0.69	1.23	0.99	1.02	1.09	13.16	8.72
40	Tata India Pharma & HealthCare Fund - Direct Plan	0.94	0.81	6.49	0.67	1.20	55.36	NA

aa.mf$plus_ctr <- 0 
aa.mf$plus_factors <- ""


filter_ctr <- function(a1.mf, values.rx ){
  
  a1.mf$plus_ctr <- 0 
  a1.mf$plus_factors <- ""
  
  rsq.vx<- values.rx[1]
  beta.vx <- values.rx[2] 
  alpha.vx <- values.rx[3]
  sharpe_ratio.vx <- values.rx[4]
  expense_ratio.vx <- values.rx[5]
  
  a1.mf[a1.mf$`R-Squared` >= rsq.vx,]$plus_ctr <- 1
  a1.mf[a1.mf$`R-Squared` >= rsq.vx,]$plus_factors <- "R_Sq"
  
  a1.mf[a1.mf$Beta >= beta.vx,]$plus_ctr <- a1.mf[a1.mf$Beta >= beta.vx,]$plus_ctr +1
  a1.mf[a1.mf$Beta >= beta.vx,]$plus_factors <- paste0(a1.mf[a1.mf$Beta >= beta.vx,]$plus_factors,"-Beta")
  
  a1.mf[a1.mf$Alpha >= alpha.vx,]$plus_ctr <- a1.mf[a1.mf$Alpha >= alpha.vx,]$plus_ctr +1
  a1.mf[a1.mf$Alpha >= alpha.vx,]$plus_factors <- paste0(a1.mf[a1.mf$Alpha >= alpha.vx,]$plus_factors,"-Alpha")
  
  a1.mf[a1.mf$`Sharpe Ratio` >= sharpe_ratio.vx,]$plus_ctr <- a1.mf[a1.mf$`Sharpe Ratio` >= sharpe_ratio.vx,]$plus_ctr +1
  a1.mf[a1.mf$`Sharpe Ratio` >= sharpe_ratio.vx,]$plus_factors <- 
    paste0(a1.mf[a1.mf$`Sharpe Ratio` >= sharpe_ratio.vx,]$plus_ctr,"-Sharpe_Ratio")
  
  a1.mf[a1.mf$`Expense Ratio (%)` <= expense_ratio.vx,]$plus_ctr <- a1.mf[a1.mf$`Expense Ratio (%)` <= expense_ratio.vx,]$plus_ctr +1
  a1.mf[a1.mf$`Expense Ratio (%)` <= expense_ratio.vx,]$plus_factors <- 
    paste0(a1.mf[a1.mf$`Expense Ratio (%)` <= expense_ratio.vx,]$plus_factors, "-Exp_Ratio")
  
  a1.mf <- a1.mf[order(a1.mf$`5 Yr Ret (%)`, decreasing = TRUE),]
  
  return(a1.mf)

  
}

pandoc.header(colFmt("1B: MF's filtered on Four out of Five Criteria", 'blue'), 1, 'setext')

1B: MF’s filtered on Four out of Five Criteria

top.mf <- filter_ctr(aa.mf, max.values)
top.mf <- top.mf[top.mf$plus_ctr >= 4,]
rownames(top.mf) <- NULL
value.string <- paste0("R-Sq:",analysis.df$value[1],", Beta:-",
                       analysis.df$value[2],", Alpha:-",
                       analysis.df$value[3],", Sharpe Ratio:-",
                       analysis.df$value[4],", Expense Ratio:-",
                       analysis.df$value[5])

value.string <- paste("MF's Meeting Max Values of Four our of Five Criteria ",  value.string)
row.ctr <- nrow(top.mf)
paste(colFmt(value.string, "blue"))

[1] “MF’s Meeting Max Values of Four our of Five Criteria R-Sq:0.75, Beta:-1.1, Alpha:-2, Sharpe Ratio:-1.5, Expense Ratio:-0.015”

top.mf[1:row.ctr,c(1,37,35,36,33,6,7,22)] %>%
  mutate(
    Ser.No = row.names(.),
    Fund = ('Fund Name'),
    R_Sq = color_tile("white", "orange")(`R-Squared`),
    Beta = color_tile("white", "green")(Beta),
    Alpha = color_tile("white", "blue")(Alpha),
    Sharpe_Ratio = color_tile("white", "purple")(`Sharpe Ratio`),
    Exp_Ratio = (`Expense Ratio (%)`),
    Return_1Yr =color_tile("white", "red")(`1 Yr Ret (%).x`),
    Return_5Yr =color_tile("white", "red")(`5 Yr Ret (%)`),
    
  ) %>%
  select(Ser.No,Fund, R_Sq, Beta, Alpha, Sharpe_Ratio, Exp_Ratio, Return_1Yr, Return_5Yr) %>%
  kable(escape = F) %>%
  kable_styling("hover", full_width = T) %>%
  scroll_box(width = "100%", height = "300px")

Ser.No	Fund	R_Sq	Beta	Alpha	Sharpe_Ratio	Exp_Ratio	Return_1Yr	Return_5Yr
1	Fund Name	0.88	0.80	3.46	1.67	0.48	13.96	11.20
2	Fund Name	0.88	0.80	3.36	1.65	0.61	13.81	11.06
3	Fund Name	0.76	0.63	2.88	1.59	0.33	12.09	10.86
4	Fund Name	0.76	0.63	2.55	1.50	0.64	11.75	10.49
5	Fund Name	0.67	1.14	2.77	1.64	0.45	12.30	10.31
6	Fund Name	0.06	2.57	7.95	1.58	0.20	14.08	9.38
7	Fund Name	0.05	1.52	5.43	1.75	0.35	11.15	9.32
8	Fund Name	0.04	1.46	5.57	1.68	0.34	10.94	9.18
9	Fund Name	0.11	2.36	6.58	1.77	0.31	11.27	9.11
10	Fund Name	0.06	1.42	5.37	2.12	0.34	10.85	9.06
11	Fund Name	0.04	1.11	5.05	2.20	0.30	11.01	9.05
12	Fund Name	0.04	1.26	5.54	2.04	0.34	10.91	9.01
13	Fund Name	0.13	2.58	6.63	1.69	0.19	9.62	8.99
14	Fund Name	0.05	1.53	5.13	1.61	0.68	10.78	8.98
15	Fund Name	0.13	2.23	6.52	2.07	0.31	9.86	8.94
16	Fund Name	0.14	2.52	6.30	1.62	0.32	10.88	8.92
17	Fund Name	0.05	1.49	5.05	1.66	0.21	10.75	8.87
18	Fund Name	0.13	2.78	7.39	1.79	0.30	11.21	8.86
19	Fund Name	0.17	2.52	6.81	2.05	0.30	6.49	8.84
20	Fund Name	0.11	2.20	6.09	1.72	0.17	10.90	8.83
21	Fund Name	0.08	1.92	5.74	1.66	0.32	10.58	8.81
22	Fund Name	0.04	1.48	5.24	1.53	0.76	10.55	8.80
23	Fund Name	0.11	2.37	6.20	1.60	0.80	10.73	8.77
24	Fund Name	0.12	2.01	5.55	1.77	0.34	10.30	8.74
25	Fund Name	0.13	2.24	6.24	1.93	0.62	9.53	8.68
26	Fund Name	0.09	1.71	5.41	1.90	0.28	10.26	8.67
27	Fund Name	0.09	1.55	5.44	2.26	0.28	9.23	8.64
28	Fund Name	0.06	1.44	4.74	1.71	0.34	10.19	8.64
29	Fund Name	0.13	2.79	7.11	1.68	0.65	10.82	8.61
30	Fund Name	0.10	1.89	5.21	1.65	0.30	9.99	8.60
31	Fund Name	0.13	2.50	5.98	1.50	0.54	10.58	8.59
32	Fund Name	0.17	2.67	6.75	1.86	0.75	5.98	8.59
33	Fund Name	0.06	1.23	4.25	1.81	0.42	9.74	8.57
34	Fund Name	0.13	2.57	6.26	1.54	0.50	9.27	8.57
35	Fund Name	0.17	2.22	5.83	2.01	0.25	10.10	8.52
36	Fund Name	0.07	1.76	5.23	1.61	0.40	10.19	8.43
37	Fund Name	0.04	1.26	5.05	1.80	0.81	10.39	8.43
38	Fund Name	0.11	2.20	5.69	1.54	0.55	10.47	8.38
39	Fund Name	0.04	1.13	4.40	1.81	1.01	10.25	8.30
40	Fund Name	0.06	1.41	4.53	1.66	1.14	9.95	8.12
41	Fund Name	0.09	1.72	4.91	1.63	0.80	9.69	8.11
42	Fund Name	0.10	1.17	3.98	2.32	0.21	8.36	7.99
43	Fund Name	0.17	2.21	5.33	1.72	0.75	9.56	7.98
44	Fund Name	0.09	1.55	4.87	1.92	0.83	8.65	7.97
45	Fund Name	0.17	1.13	3.72	2.83	0.28	7.40	7.92
46	Fund Name	0.37	1.17	3.36	3.39	0.24	6.05	7.88
47	Fund Name	0.40	1.37	3.86	3.39	0.13	6.49	7.77
48	Fund Name	0.42	1.11	3.08	3.43	0.33	5.52	7.76
49	Fund Name	0.17	1.13	3.50	2.59	0.51	7.16	7.72
50	Fund Name	0.54	1.41	3.52	3.22	0.11	6.00	7.72
51	Fund Name	0.22	1.14	3.42	2.83	0.30	6.87	7.62
52	Fund Name	0.45	1.35	3.51	3.15	0.23	6.12	7.59
53	Fund Name	0.22	1.18	3.58	2.87	1.10	6.96	7.56
54	Fund Name	0.42	1.10	2.86	3.06	0.58	5.27	7.54
55	Fund Name	0.40	1.37	3.68	3.13	0.28	6.33	7.53
56	Fund Name	0.23	1.14	3.20	2.55	0.55	6.61	7.40
57	Fund Name	0.37	1.18	2.84	2.51	0.89	5.40	7.39
58	Fund Name	0.44	1.34	3.18	2.68	0.39	5.82	7.24
59	Fund Name	0.10	1.16	3.21	1.68	1.00	7.47	7.23
60	Fund Name	0.55	1.44	3.12	2.48	0.66	5.46	7.22
61	Fund Name	0.30	1.14	2.80	2.31	0.20	6.13	7.19
62	Fund Name	0.29	1.38	3.60	2.52	0.23	6.19	6.99
63	Fund Name	0.22	1.31	2.82	1.57	0.29	5.77	6.97
64	Fund Name	0.28	1.38	3.35	2.25	0.46	5.97	6.73

top.mf <- filter_ctr(aa.mf, min.values)
top.mf <- top.mf[top.mf$plus_ctr >= 4,]
rownames(top.mf) <- NULL
value.string <- paste0("R-Sq:",analysis.df$min[1],", Beta:-",
                       analysis.df$min[2],", Alpha:-",
                       analysis.df$min[3],", Sharpe Ratio:-",
                       analysis.df$min[4],", Expense Ratio:-",
                       analysis.df$min[5])
value.string <- paste("MF's Meeting Min Values of Four our of Five Criteria ",  value.string)
row.ctr <- nrow(top.mf)
paste(colFmt(value.string, "blue"))

[1] “MF’s Meeting Min Values of Four our of Five Criteria R-Sq:0.6, Beta:-1, Alpha:-1.4, Sharpe Ratio:-0.75, Expense Ratio:-0.025”

top.mf[1:row.ctr,c(1,37,35,36,33,6,7,22)] %>%
  mutate(
    Ser.No = row.names(.),
    Fund = ('Fund Name'),
    R_Sq = color_tile("white", "orange")(`R-Squared`),
    Beta = color_tile("white", "green")(Beta),
    Alpha = color_tile("white", "blue")(Alpha),
    Sharpe_Ratio = color_tile("white", "purple")(`Sharpe Ratio`),
    Exp_Ratio = (`Expense Ratio (%)`),
    Return_1Yr =color_tile("white", "red")(`1 Yr Ret (%).x`),
    Return_5Yr =color_tile("white", "red")(`5 Yr Ret (%)`),
    
  ) %>%
  select(Ser.No,Fund, R_Sq, Beta, Alpha, Sharpe_Ratio, Exp_Ratio, Return_1Yr, Return_5Yr) %>%
  kable(escape = F) %>%
  kable_styling("hover", full_width = T) %>%
  scroll_box(width = "100%", height = "300px")

Ser.No	Fund	R_Sq	Beta	Alpha	Sharpe_Ratio	Exp_Ratio	Return_1Yr	Return_5Yr
1	Fund Name	0.83	1.01	6.96	0.31	1.46	27.17	17.78
2	Fund Name	0.95	1.02	3.18	0.19	0.79	16.77	17.25
3	Fund Name	0.88	1.00	5.95	0.27	0.57	25.68	16.71
4	Fund Name	0.95	1.02	2.27	0.15	1.74	15.62	16.24
5	Fund Name	0.89	1.00	4.83	0.23	2.48	23.44	15.89
6	Fund Name	0.89	1.04	6.89	0.30	0.90	18.68	15.85
7	Fund Name	0.89	1.04	5.42	0.24	2.22	17.04	14.37
8	Fund Name	0.95	1.01	4.86	0.23	0.52	25.97	12.94
9	Fund Name	0.99	1.00	2.94	0.21	0.07	9.48	12.50
10	Fund Name	0.99	1.00	2.90	0.20	0.07	9.39	12.44
11	Fund Name	0.99	1.00	2.92	0.21	0.07	9.46	12.44
12	Fund Name	0.99	1.00	2.71	0.20	0.28	9.21	12.22
13	Fund Name	0.99	1.00	2.61	0.19	0.10	8.92	12.20
14	Fund Name	0.99	1.00	2.42	0.18	0.30	8.64	12.00
15	Fund Name	0.69	1.58	3.05	0.44	0.34	19.23	11.73
16	Fund Name	0.88	0.80	3.46	1.67	0.48	13.96	11.20
17	Fund Name	0.93	0.77	1.77	1.32	0.62	12.47	11.11
18	Fund Name	0.88	0.80	3.36	1.65	0.61	13.81	11.06
19	Fund Name	0.69	1.58	2.32	0.38	1.05	18.69	10.96
20	Fund Name	0.76	0.63	2.88	1.59	0.33	12.09	10.86
21	Fund Name	0.87	0.82	2.23	1.36	0.23	14.09	10.84
22	Fund Name	0.87	0.82	2.03	1.31	0.39	13.91	10.60
23	Fund Name	0.90	0.84	1.89	1.30	0.61	14.89	10.55
24	Fund Name	0.76	0.63	2.55	1.50	0.64	11.75	10.49
25	Fund Name	0.68	1.08	2.28	1.54	0.80	13.42	10.36
26	Fund Name	0.88	0.79	1.73	1.27	0.54	13.86	10.31
27	Fund Name	0.13	5.39	10.47	0.99	1.39	12.80	10.31
28	Fund Name	0.67	1.14	2.77	1.64	0.45	12.30	10.31
29	Fund Name	0.80	1.51	1.61	1.22	0.87	12.01	9.97
30	Fund Name	0.84	1.77	1.61	1.17	0.86	13.89	9.95
31	Fund Name	0.62	1.12	2.31	1.45	0.85	14.26	9.95
32	Fund Name	0.68	1.33	2.42	1.42	0.25	13.78	9.85
33	Fund Name	0.84	1.36	1.30	1.20	0.87	10.21	9.70
34	Fund Name	0.67	1.14	2.15	1.43	1.15	11.56	9.63
35	Fund Name	0.69	0.59	2.34	1.41	0.89	13.32	9.60
36	Fund Name	0.68	1.08	1.58	1.28	1.52	12.66	9.59
37	Fund Name	0.14	5.41	9.93	0.86	1.99	12.24	9.53
38	Fund Name	0.84	0.67	1.57	1.27	0.76	11.64	9.49
39	Fund Name	0.86	1.75	1.07	1.06	0.72	11.62	9.44
40	Fund Name	0.06	2.57	7.95	1.58	0.20	14.08	9.38
41	Fund Name	0.85	1.78	0.86	1.00	1.35	12.22	9.36
42	Fund Name	0.84	1.38	1.41	1.23	0.96	10.97	9.35
43	Fund Name	0.05	1.52	5.43	1.75	0.35	11.15	9.32
44	Fund Name	0.79	1.64	1.00	1.01	0.42	12.94	9.21
45	Fund Name	0.71	1.63	1.87	1.18	0.29	13.62	9.19
46	Fund Name	0.79	1.52	0.87	1.00	1.64	11.27	9.19
47	Fund Name	0.04	1.46	5.57	1.68	0.34	10.94	9.18
48	Fund Name	0.62	1.12	1.57	1.20	1.47	13.57	9.18
49	Fund Name	0.61	1.13	1.83	1.27	0.56	12.46	9.14
50	Fund Name	0.02	1.11	4.69	1.39	0.36	11.01	9.12
51	Fund Name	0.11	2.36	6.58	1.77	0.31	11.27	9.11
52	Fund Name	0.69	0.59	1.87	1.28	1.36	12.82	9.08
53	Fund Name	0.84	1.77	0.86	0.99	1.70	13.00	9.08
54	Fund Name	0.06	2.59	7.69	1.49	0.55	13.68	9.07
55	Fund Name	0.51	1.36	1.77	1.06	0.49	13.39	9.06
56	Fund Name	0.06	1.42	5.37	2.12	0.34	10.85	9.06
57	Fund Name	0.04	1.11	5.05	2.20	0.30	11.01	9.05
58	Fund Name	0.80	1.37	1.34	1.18	0.75	11.24	9.02
59	Fund Name	0.04	1.26	5.54	2.04	0.34	10.91	9.01
60	Fund Name	0.13	2.58	6.63	1.69	0.19	9.62	8.99
61	Fund Name	0.05	1.53	5.13	1.61	0.68	10.78	8.98
62	Fund Name	0.67	1.34	1.71	1.20	0.67	13.29	8.98
63	Fund Name	0.13	2.23	6.52	2.07	0.31	9.86	8.94
64	Fund Name	0.02	1.03	4.18	1.40	0.37	10.27	8.94
65	Fund Name	0.71	1.08	0.65	0.96	0.63	10.64	8.94
66	Fund Name	0.14	2.52	6.30	1.62	0.32	10.88	8.92
67	Fund Name	0.81	1.57	0.97	1.03	0.80	12.66	8.88
68	Fund Name	0.05	1.49	5.05	1.66	0.21	10.75	8.87
69	Fund Name	0.13	2.78	7.39	1.79	0.30	11.21	8.86
70	Fund Name	0.69	0.95	1.97	1.54	0.76	10.97	8.86
71	Fund Name	0.17	2.52	6.81	2.05	0.30	6.49	8.84
72	Fund Name	0.11	2.20	6.09	1.72	0.17	10.90	8.83
73	Fund Name	0.71	1.08	0.54	0.92	0.75	10.49	8.83
74	Fund Name	0.08	1.92	5.74	1.66	0.32	10.58	8.81
75	Fund Name	0.04	1.48	5.24	1.53	0.76	10.55	8.80
76	Fund Name	0.11	2.37	6.20	1.60	0.80	10.73	8.77
77	Fund Name	0.12	2.01	5.55	1.77	0.34	10.30	8.74
78	Fund Name	0.69	1.23	0.99	1.02	1.09	13.16	8.72
79	Fund Name	0.13	2.24	6.24	1.93	0.62	9.53	8.68
80	Fund Name	0.02	1.11	4.24	1.21	0.81	10.51	8.68
81	Fund Name	0.09	1.71	5.41	1.90	0.28	10.26	8.67
82	Fund Name	0.74	1.64	0.10	0.76	0.25	11.18	8.65
83	Fund Name	0.09	1.55	5.44	2.26	0.28	9.23	8.64
84	Fund Name	0.06	1.44	4.74	1.71	0.34	10.19	8.64
85	Fund Name	0.13	2.79	7.11	1.68	0.65	10.82	8.61
86	Fund Name	0.10	1.89	5.21	1.65	0.30	9.99	8.60
87	Fund Name	0.83	1.43	-0.02	0.77	0.88	10.24	8.59
88	Fund Name	0.13	2.50	5.98	1.50	0.54	10.58	8.59
89	Fund Name	0.71	1.63	1.57	1.11	0.63	13.25	8.59
90	Fund Name	0.83	1.36	0.42	0.91	1.76	9.20	8.59
91	Fund Name	0.17	2.67	6.75	1.86	0.75	5.98	8.59
92	Fund Name	0.06	1.23	4.25	1.81	0.42	9.74	8.57
93	Fund Name	0.13	2.57	6.26	1.54	0.50	9.27	8.57
94	Fund Name	0.85	1.78	0.21	0.84	1.97	11.53	8.57
95	Fund Name	0.61	1.13	1.27	1.08	1.13	11.87	8.56
96	Fund Name	0.02	1.04	3.76	1.21	0.83	9.78	8.55
97	Fund Name	0.86	1.76	0.29	0.86	1.76	10.72	8.55
98	Fund Name	0.62	0.77	1.84	1.57	0.35	10.38	8.54
99	Fund Name	0.80	1.23	0.33	0.88	0.51	10.39	8.53
100	Fund Name	0.48	1.05	1.82	1.17	0.40	9.25	8.53
101	Fund Name	0.17	2.22	5.83	2.01	0.25	10.10	8.52
102	Fund Name	0.84	1.38	0.64	0.98	1.62	10.24	8.48
103	Fund Name	0.07	1.76	5.23	1.61	0.40	10.19	8.43
104	Fund Name	0.04	1.26	5.05	1.80	0.81	10.39	8.43
105	Fund Name	0.78	1.64	0.30	0.83	0.89	12.34	8.39
106	Fund Name	0.11	2.20	5.69	1.54	0.55	10.47	8.38
107	Fund Name	0.05	1.49	4.63	1.46	0.61	10.31	8.37
108	Fund Name	0.63	1.02	0.63	0.91	0.16	10.54	8.33
109	Fund Name	0.04	1.13	4.40	1.81	1.01	10.25	8.30
110	Fund Name	0.08	1.92	5.23	1.43	0.78	10.06	8.27
111	Fund Name	0.02	1.00	4.95	1.63	0.23	10.13	8.16
112	Fund Name	0.63	1.21	1.17	1.04	0.23	7.54	8.15
113	Fund Name	0.11	2.01	5.00	1.48	0.84	9.75	8.15
114	Fund Name	0.06	1.41	4.53	1.66	1.14	9.95	8.12
115	Fund Name	0.09	1.72	4.91	1.63	0.80	9.69	8.11
116	Fund Name	0.80	1.36	0.35	0.87	1.88	10.05	8.03
117	Fund Name	0.11	1.05	3.90	2.75	0.32	7.71	8.03
118	Fund Name	0.10	1.17	3.98	2.32	0.21	8.36	7.99
119	Fund Name	0.17	2.21	5.33	1.72	0.75	9.56	7.98
120	Fund Name	0.09	1.55	4.87	1.92	0.83	8.65	7.97
121	Fund Name	0.87	1.45	0.16	0.85	0.18	9.94	7.96
122	Fund Name	0.14	1.71	3.86	1.37	0.13	8.16	7.95
123	Fund Name	0.85	1.54	0.06	0.80	0.95	9.43	7.92
124	Fund Name	0.17	1.13	3.72	2.83	0.28	7.40	7.92
125	Fund Name	0.06	1.46	4.03	1.33	1.24	9.30	7.91
126	Fund Name	0.37	1.17	3.36	3.39	0.24	6.05	7.88
127	Fund Name	0.90	1.66	0.08	0.83	1.23	9.84	7.87
128	Fund Name	0.81	1.57	-0.01	0.76	1.54	11.46	7.86
129	Fund Name	0.19	1.08	3.82	3.27	0.40	7.62	7.83
130	Fund Name	0.85	1.46	0.29	0.87	1.28	11.15	7.79
131	Fund Name	0.06	1.22	3.54	1.38	1.02	9.04	7.78
132	Fund Name	0.10	1.88	4.47	1.28	0.93	9.29	7.77
133	Fund Name	0.40	1.37	3.86	3.39	0.13	6.49	7.77
134	Fund Name	0.42	1.11	3.08	3.43	0.33	5.52	7.76
135	Fund Name	0.19	2.60	5.33	1.32	0.23	7.96	7.75
136	Fund Name	0.17	1.13	3.50	2.59	0.51	7.16	7.72
137	Fund Name	0.54	1.41	3.52	3.22	0.11	6.00	7.72
138	Fund Name	0.33	1.08	3.45	3.79	0.32	6.62	7.68
139	Fund Name	0.19	2.60	5.20	1.25	0.36	7.82	7.66
140	Fund Name	0.12	1.06	3.60	2.45	0.65	7.38	7.65
141	Fund Name	0.22	1.14	3.42	2.83	0.30	6.87	7.62
142	Fund Name	0.07	1.75	4.37	1.20	1.25	9.26	7.61
143	Fund Name	0.45	1.35	3.51	3.15	0.23	6.12	7.59
144	Fund Name	0.22	1.18	3.58	2.87	1.10	6.96	7.56
145	Fund Name	0.42	1.10	2.86	3.06	0.58	5.27	7.54
146	Fund Name	0.40	1.37	3.68	3.13	0.28	6.33	7.53
147	Fund Name	0.27	1.02	3.56	3.90	0.21	7.00	7.50
148	Fund Name	0.39	1.03	3.46	4.42	0.15	6.38	7.44
149	Fund Name	0.23	1.14	3.20	2.55	0.55	6.61	7.40
150	Fund Name	0.37	1.18	2.84	2.51	0.89	5.40	7.39
151	Fund Name	0.63	1.20	0.54	0.85	0.98	6.74	7.36
152	Fund Name	0.39	1.03	3.36	4.24	0.25	6.27	7.33
153	Fund Name	0.50	1.06	3.29	4.45	0.22	6.07	7.32
154	Fund Name	0.27	1.01	3.36	3.61	0.35	6.81	7.29
155	Fund Name	0.33	1.08	3.06	3.14	0.76	6.15	7.28
156	Fund Name	0.50	1.07	3.23	4.30	0.32	5.97	7.26
157	Fund Name	0.85	1.46	0.01	0.79	1.49	10.83	7.26
158	Fund Name	0.44	1.34	3.18	2.68	0.39	5.82	7.24
159	Fund Name	0.10	1.16	3.21	1.68	1.00	7.47	7.23
160	Fund Name	0.55	1.44	3.12	2.48	0.66	5.46	7.22
161	Fund Name	0.30	1.14	2.80	2.31	0.20	6.13	7.19
162	Fund Name	0.29	1.38	3.60	2.52	0.23	6.19	6.99
163	Fund Name	0.22	1.31	2.82	1.57	0.29	5.77	6.97
164	Fund Name	0.28	1.38	3.35	2.25	0.46	5.97	6.73
165	Fund Name	0.19	1.02	2.45	1.80	0.40	5.19	6.62
166	Fund Name	0.31	1.16	2.12	1.30	0.97	5.31	6.50
167	Fund Name	0.22	1.30	2.08	0.75	1.01	5.03	6.20
168	Fund Name	0.19	1.02	1.76	0.88	1.10	4.42	5.92
169	Fund Name	0.87	1.00	9.52	-0.29	2.19	-3.91	4.97
170	Fund Name	0.92	1.07	4.11	-0.52	1.44	-6.98	4.60
171	Fund Name	0.90	1.02	4.25	-0.50	1.83	-3.68	3.19
172	Fund Name	0.99	1.00	2.91	0.21	0.05	9.39	NA
173	Fund Name	0.99	1.00	2.99	0.21	0.10	9.50	NA
174	Fund Name	0.67	1.22	2.11	1.38	0.49	11.40	NA
175	Fund Name	0.67	1.23	0.84	0.96	1.39	10.37	NA
176	Fund Name	0.98	1.01	4.86	0.24	0.36	16.30	NA
177	Fund Name	0.98	1.01	3.41	0.17	1.77	14.54	NA
178	Fund Name	0.85	1.06	3.62	0.16	0.88	16.81	NA
179	Fund Name	0.85	1.06	2.88	0.13	1.38	16.23	NA

top.mf <- filter_ctr(aa.mf, avg.values)
top.mf <- top.mf[top.mf$plus_ctr >= 4,]
rownames(top.mf) <- NULL
value.string <- paste0("R-Sq:",round(analysis.df$avg[1], digits = 2),", Beta:-",
                       round(analysis.df$avg[2], digits = 2),", Alpha:-",
                       round(analysis.df$avg[3], digits = 2),", Sharpe Ratio:-",
                       round(analysis.df$avg[4], digits = 2),", Expense Ratio:-",
                       round(analysis.df$avg[5], digits = 2))
value.string <- paste("MF's Meeting Average Values of Four our of Five Criteria ",  value.string)
row.ctr <- nrow(top.mf)
paste(colFmt(value.string, "blue"))

[1] “MF’s Meeting Average Values of Four our of Five Criteria R-Sq:0.68, Beta:-0.76, Alpha:–0.46, Sharpe Ratio:-0.44, Expense Ratio:-1.21”

top.mf[1:row.ctr,c(1,37,35,36,33,6,7,22)] %>%
  mutate(
    Ser.No = row.names(.),
    Fund = ('Fund Name'),
    R_Sq = color_tile("white", "orange")(`R-Squared`),
    Beta = color_tile("white", "green")(Beta),
    Alpha = color_tile("white", "blue")(Alpha),
    Sharpe_Ratio = color_tile("white", "purple")(`Sharpe Ratio`),
    Exp_Ratio = (`Expense Ratio (%)`),
    Return_1Yr =color_tile("white", "red")(`1 Yr Ret (%).x`),
    Return_5Yr =color_tile("white", "red")(`5 Yr Ret (%)`),
    
  ) %>%
  select(Ser.No,Fund, R_Sq, Beta, Alpha, Sharpe_Ratio, Exp_Ratio, Return_1Yr, Return_5Yr) %>%
  kable(escape = F) %>%
  kable_styling("hover", full_width = T) %>%
  scroll_box(width = "100%", height = "300px")

Ser.No	Fund	R_Sq	Beta	Alpha	Sharpe_Ratio	Exp_Ratio	Return_1Yr	Return_5Yr
1	Fund Name	0.82	0.93	10.62	0.49	0.88	29.97	18.04
2	Fund Name	0.81	0.84	0.45	0.95	1.59	47.09	17.61
3	Fund Name	0.82	0.93	9.92	0.46	1.38	29.33	17.50
4	Fund Name	0.93	0.89	5.53	0.17	1.10	0.72	17.39
5	Fund Name	0.95	1.02	3.18	0.19	0.79	16.77	17.25
6	Fund Name	0.87	0.93	-0.34	0.95	1.96	51.39	16.72
7	Fund Name	0.88	1.00	5.95	0.27	0.57	25.68	16.71
8	Fund Name	0.89	1.04	6.89	0.30	0.90	18.68	15.85
9	Fund Name	0.90	0.94	4.79	0.24	0.66	9.64	15.81
10	Fund Name	0.92	0.83	10.11	0.13	0.96	17.26	15.58
11	Fund Name	0.85	0.79	7.92	0.44	1.01	27.25	15.13
12	Fund Name	0.95	0.84	1.83	0.05	1.16	-0.66	15.05
13	Fund Name	0.92	0.78	0.15	1.00	1.69	37.09	14.79
14	Fund Name	0.91	0.99	0.93	0.09	0.77	18.35	14.18
15	Fund Name	0.90	0.77	5.72	0.12	1.10	7.45	14.11
16	Fund Name	0.94	1.02	1.36	0.13	0.56	14.38	14.09
17	Fund Name	0.97	0.86	4.75	0.33	0.87	16.45	14.08
18	Fund Name	0.91	0.98	1.27	0.07	0.80	8.91	13.84
19	Fund Name	0.94	0.92	1.54	0.09	0.84	8.74	13.84
20	Fund Name	0.99	0.99	0.80	0.11	0.58	9.42	13.80
21	Fund Name	0.96	0.84	2.94	0.08	0.90	17.37	13.73
22	Fund Name	0.88	0.95	0.43	0.07	0.95	8.19	13.60
23	Fund Name	0.86	0.97	7.18	0.33	0.57	20.47	13.55
24	Fund Name	0.92	0.79	6.81	0.16	0.64	4.09	13.40
25	Fund Name	0.98	0.89	0.73	0.17	0.39	11.12	13.37
26	Fund Name	0.97	0.99	1.37	0.13	1.05	8.23	13.36
27	Fund Name	0.90	0.85	4.08	0.23	0.88	8.49	13.33
28	Fund Name	0.84	0.88	4.05	0.21	0.81	8.54	13.05
29	Fund Name	0.95	1.01	4.86	0.23	0.52	25.97	12.94
30	Fund Name	0.95	0.85	4.06	0.13	0.74	17.49	12.78
31	Fund Name	0.96	0.95	0.43	0.07	0.82	10.34	12.68
32	Fund Name	0.96	0.86	4.28	0.24	0.86	16.09	12.67
33	Fund Name	0.97	0.92	2.46	0.05	0.61	13.65	12.64
34	Fund Name	0.92	0.94	2.00	0.16	0.81	12.10	12.63
35	Fund Name	0.98	0.95	0.56	0.04	0.70	6.21	12.60
36	Fund Name	0.97	0.96	2.74	0.15	1.00	10.45	12.51
37	Fund Name	0.99	1.00	2.94	0.21	0.07	9.48	12.50
38	Fund Name	0.96	0.95	1.29	0.11	0.54	5.57	12.46
39	Fund Name	0.97	1.01	0.15	0.02	0.93	7.44	12.44
40	Fund Name	0.99	1.00	2.90	0.20	0.07	9.39	12.44
41	Fund Name	0.99	1.00	2.92	0.21	0.07	9.46	12.44
42	Fund Name	0.96	0.99	-0.05	0.01	0.73	7.68	12.37
43	Fund Name	0.92	0.98	2.12	0.11	0.98	9.65	12.36
44	Fund Name	0.99	0.99	2.87	0.20	0.08	9.51	12.36
45	Fund Name	0.93	0.77	2.34	0.29	0.85	15.14	12.24
46	Fund Name	0.99	1.00	2.71	0.20	0.28	9.21	12.22
47	Fund Name	0.99	1.00	2.61	0.19	0.10	8.92	12.20
48	Fund Name	0.99	0.98	2.78	0.20	0.05	9.43	12.18
49	Fund Name	0.97	0.89	9.39	0.08	0.70	22.08	12.13
50	Fund Name	0.96	0.95	1.41	0.08	0.94	9.32	12.11
51	Fund Name	0.99	1.00	2.42	0.18	0.30	8.64	12.00
52	Fund Name	0.89	0.95	-0.06	0.01	0.84	12.07	11.98
53	Fund Name	0.99	1.01	1.03	0.12	0.07	7.86	11.96
54	Fund Name	0.99	0.98	2.67	0.20	0.10	9.36	11.94
55	Fund Name	0.98	0.98	1.95	0.16	1.05	10.18	11.90
56	Fund Name	0.97	0.92	6.63	-0.03	1.18	15.28	11.89
57	Fund Name	0.97	0.93	0.39	0.03	0.69	9.25	11.86
58	Fund Name	0.69	1.58	3.05	0.44	0.34	19.23	11.73
59	Fund Name	1.00	1.01	1.01	0.11	0.07	8.16	11.73
60	Fund Name	1.00	1.01	1.02	0.12	0.07	8.18	11.69
61	Fund Name	0.96	0.94	1.33	0.12	0.91	11.78	11.66
62	Fund Name	1.00	1.01	0.95	0.11	0.10	8.16	11.63
63	Fund Name	0.99	1.01	1.00	0.11	0.05	8.22	11.62
64	Fund Name	0.86	0.92	0.13	0.12	0.87	10.40	11.60
65	Fund Name	0.98	0.97	2.26	0.18	1.00	8.40	11.59
66	Fund Name	0.99	0.99	1.06	0.12	0.15	8.94	11.55
67	Fund Name	1.00	1.01	1.05	0.12	0.05	8.24	11.55
68	Fund Name	0.96	0.84	1.41	0.14	1.08	9.65	11.54
69	Fund Name	1.00	1.00	0.91	0.11	0.05	8.23	11.52
70	Fund Name	0.99	0.99	2.30	0.18	0.57	9.16	11.51
71	Fund Name	1.00	1.01	0.91	0.11	0.09	8.12	11.49
72	Fund Name	0.95	0.92	2.28	0.04	0.71	17.43	11.43
73	Fund Name	0.99	0.99	0.93	0.11	0.30	8.75	11.42
74	Fund Name	1.00	1.01	0.85	0.11	0.10	8.03	11.42
75	Fund Name	1.00	1.01	0.80	0.10	0.10	7.81	11.34
76	Fund Name	1.00	1.01	0.79	0.10	0.14	7.97	11.34
77	Fund Name	0.99	0.98	0.80	0.11	0.05	8.00	11.32
78	Fund Name	1.00	1.00	-0.22	0.06	0.14	8.14	11.31
79	Fund Name	0.99	0.96	0.92	0.11	0.93	9.09	11.28
80	Fund Name	0.99	0.98	2.04	0.17	0.61	8.94	11.27
81	Fund Name	1.00	1.01	0.92	0.11	0.12	8.08	11.25
82	Fund Name	0.94	1.06	0.15	0.06	0.85	0.01	11.24
83	Fund Name	0.88	0.80	3.46	1.67	0.48	13.96	11.20
84	Fund Name	1.00	1.01	0.60	0.10	0.09	7.55	11.20
85	Fund Name	0.99	1.00	0.67	0.10	0.10	8.13	11.18
86	Fund Name	0.99	0.97	1.24	0.13	1.05	10.57	11.16
87	Fund Name	1.00	1.01	0.61	0.10	0.30	7.61	11.15
88	Fund Name	0.92	1.01	-0.16	0.11	0.92	10.96	11.13
89	Fund Name	0.99	1.00	0.69	0.10	0.10	7.95	11.12
90	Fund Name	1.00	1.00	0.72	0.10	0.30	8.06	11.11
91	Fund Name	0.93	0.77	1.77	1.32	0.62	12.47	11.11
92	Fund Name	0.88	0.80	3.36	1.65	0.61	13.81	11.06
93	Fund Name	1.00	0.98	-0.29	0.05	0.46	7.45	11.04
94	Fund Name	0.90	0.86	2.31	0.26	0.78	12.44	10.98
95	Fund Name	0.99	0.99	1.85	0.16	1.08	8.82	10.97
96	Fund Name	0.69	1.58	2.32	0.38	1.05	18.69	10.96
97	Fund Name	0.93	0.94	5.78	0.18	0.69	38.23	10.93
98	Fund Name	0.52	0.81	3.21	1.98	0.73	13.41	10.90
99	Fund Name	1.00	1.01	0.68	0.10	0.05	7.91	10.86
100	Fund Name	0.76	0.63	2.88	1.59	0.33	12.09	10.86
101	Fund Name	0.96	0.99	0.74	0.08	1.13	8.07	10.86
102	Fund Name	0.87	0.82	2.23	1.36	0.23	14.09	10.84
103	Fund Name	0.95	0.88	0.13	0.13	1.08	5.57	10.84
104	Fund Name	0.99	0.99	0.26	0.08	0.26	7.81	10.81
105	Fund Name	0.99	0.93	0.65	0.10	1.07	12.75	10.81
106	Fund Name	0.99	0.98	0.37	0.08	0.50	7.36	10.80
107	Fund Name	0.99	1.01	0.34	0.08	0.48	7.88	10.76
108	Fund Name	0.99	1.00	0.26	0.08	0.45	7.71	10.75
109	Fund Name	0.99	0.99	0.20	0.08	0.33	7.89	10.71
110	Fund Name	1.00	1.01	0.18	0.08	0.48	7.09	10.71
111	Fund Name	0.94	0.83	0.32	0.03	1.13	11.90	10.69
112	Fund Name	0.91	0.82	-0.32	0.09	1.03	6.83	10.67
113	Fund Name	0.87	0.82	2.03	1.31	0.39	13.91	10.60
114	Fund Name	0.95	0.85	7.88	0.72	1.16	58.29	10.56
115	Fund Name	0.99	0.96	0.59	0.10	1.11	8.90	10.56
116	Fund Name	0.90	0.84	1.89	1.30	0.61	14.89	10.55
117	Fund Name	0.95	0.93	2.89	0.07	1.21	14.90	10.54
118	Fund Name	0.97	0.85	-0.07	-0.27	0.83	4.00	10.52
119	Fund Name	0.76	0.63	2.55	1.50	0.64	11.75	10.49
120	Fund Name	0.99	0.99	0.00	0.07	0.58	7.71	10.46
121	Fund Name	0.96	0.87	3.89	-0.12	0.91	5.66	10.40
122	Fund Name	0.98	0.93	-0.46	0.04	0.90	6.49	10.39
123	Fund Name	0.68	1.08	2.28	1.54	0.80	13.42	10.36
124	Fund Name	0.84	0.77	0.84	1.03	0.58	12.40	10.33
125	Fund Name	0.99	0.99	-0.19	0.06	0.67	7.27	10.32
126	Fund Name	0.99	1.00	-0.12	0.06	1.18	6.85	10.32
127	Fund Name	0.88	0.79	1.73	1.27	0.54	13.86	10.31
128	Fund Name	0.67	1.14	2.77	1.64	0.45	12.30	10.31
129	Fund Name	0.96	0.86	-0.28	-0.06	1.08	8.16	10.28
130	Fund Name	0.83	0.61	1.83	0.63	1.13	10.37	10.23
131	Fund Name	0.99	1.00	-0.15	0.06	1.03	7.48	10.22
132	Fund Name	0.87	0.75	1.02	1.11	0.47	12.92	10.22
133	Fund Name	0.77	0.72	1.03	1.05	0.60	14.11	10.14
134	Fund Name	0.83	0.87	0.53	0.30	1.05	10.48	10.09
135	Fund Name	0.92	0.77	0.80	1.08	1.59	11.42	9.98
136	Fund Name	0.92	0.77	0.81	1.08	1.71	11.43	9.98
137	Fund Name	0.80	1.51	1.61	1.22	0.87	12.01	9.97
138	Fund Name	0.84	1.77	1.61	1.17	0.86	13.89	9.95
139	Fund Name	0.62	1.12	2.31	1.45	0.85	14.26	9.95
140	Fund Name	0.86	0.82	0.83	1.04	0.45	13.38	9.94
141	Fund Name	0.86	0.82	0.83	1.04	0.40	13.38	9.94
142	Fund Name	1.00	1.00	-0.26	0.05	1.03	7.17	9.92
143	Fund Name	0.90	0.84	1.29	1.16	1.23	14.19	9.90
144	Fund Name	0.83	0.90	0.91	0.35	1.10	11.65	9.87
145	Fund Name	0.68	1.33	2.42	1.42	0.25	13.78	9.85
146	Fund Name	0.84	0.77	0.25	0.90	1.18	11.72	9.73
147	Fund Name	0.84	1.36	1.30	1.20	0.87	10.21	9.70
148	Fund Name	0.97	0.92	5.62	-0.07	1.06	23.31	9.68
149	Fund Name	0.87	0.73	0.69	1.03	0.57	12.72	9.66
150	Fund Name	0.87	0.79	1.04	1.10	1.07	13.21	9.65
151	Fund Name	0.87	0.75	0.50	0.98	0.95	12.40	9.65
152	Fund Name	0.67	1.14	2.15	1.43	1.15	11.56	9.63
153	Fund Name	0.69	0.59	2.34	1.41	0.89	13.32	9.60
154	Fund Name	0.68	1.08	1.58	1.28	1.52	12.66	9.59
155	Fund Name	0.95	0.85	7.01	0.68	2.19	56.92	9.59
156	Fund Name	0.79	0.73	0.40	0.91	0.65	10.64	9.59
157	Fund Name	0.76	0.73	0.52	0.92	1.21	13.57	9.54
158	Fund Name	0.97	1.09	0.44	0.03	1.08	3.22	9.52
159	Fund Name	0.86	0.58	0.98	0.45	0.76	8.39	9.50
160	Fund Name	0.84	0.67	1.57	1.27	0.76	11.64	9.49
161	Fund Name	0.86	1.75	1.07	1.06	0.72	11.62	9.44
162	Fund Name	0.87	0.72	-0.25	0.79	0.44	10.72	9.43
163	Fund Name	0.06	2.57	7.95	1.58	0.20	14.08	9.38
164	Fund Name	0.02	0.83	4.73	1.98	0.40	11.50	9.38
165	Fund Name	0.79	0.75	1.01	1.05	0.40	13.45	9.36
166	Fund Name	0.85	1.78	0.86	1.00	1.35	12.22	9.36
167	Fund Name	0.84	1.38	1.41	1.23	0.96	10.97	9.35
168	Fund Name	0.87	0.91	-0.49	0.75	0.30	12.28	9.33
169	Fund Name	0.05	1.52	5.43	1.75	0.35	11.15	9.32
170	Fund Name	0.79	0.73	0.11	0.84	0.93	10.33	9.29
171	Fund Name	0.79	1.64	1.00	1.01	0.42	12.94	9.21
172	Fund Name	0.57	0.82	2.43	1.71	0.30	11.88	9.20
173	Fund Name	0.71	1.63	1.87	1.18	0.29	13.62	9.19
174	Fund Name	0.79	1.52	0.87	1.00	1.64	11.27	9.19
175	Fund Name	0.04	1.46	5.57	1.68	0.34	10.94	9.18
176	Fund Name	0.88	0.77	4.26	0.15	0.57	21.62	9.15
177	Fund Name	0.61	1.13	1.83	1.27	0.56	12.46	9.14
178	Fund Name	0.02	1.11	4.69	1.39	0.36	11.01	9.12
179	Fund Name	0.91	0.83	0.60	0.05	1.18	7.54	9.12
180	Fund Name	0.11	2.36	6.58	1.77	0.31	11.27	9.11
181	Fund Name	0.87	0.91	-0.72	0.71	0.50	12.05	9.08
182	Fund Name	0.84	1.77	0.86	0.99	1.70	13.00	9.08
183	Fund Name	0.86	0.76	2.24	0.63	0.75	13.29	9.07
184	Fund Name	0.06	2.59	7.69	1.49	0.55	13.68	9.07
185	Fund Name	0.54	0.96	1.70	1.25	0.28	11.09	9.07
186	Fund Name	0.51	1.36	1.77	1.06	0.49	13.39	9.06
187	Fund Name	0.57	0.83	2.28	1.64	0.60	11.62	9.06
188	Fund Name	0.06	1.42	5.37	2.12	0.34	10.85	9.06
189	Fund Name	0.04	1.11	5.05	2.20	0.30	11.01	9.05
190	Fund Name	0.80	1.37	1.34	1.18	0.75	11.24	9.02
191	Fund Name	0.04	1.26	5.54	2.04	0.34	10.91	9.01
192	Fund Name	0.13	2.58	6.63	1.69	0.19	9.62	8.99
193	Fund Name	0.05	1.53	5.13	1.61	0.68	10.78	8.98
194	Fund Name	0.67	1.34	1.71	1.20	0.67	13.29	8.98
195	Fund Name	0.13	2.23	6.52	2.07	0.31	9.86	8.94
196	Fund Name	0.02	1.03	4.18	1.40	0.37	10.27	8.94
197	Fund Name	0.71	1.08	0.65	0.96	0.63	10.64	8.94
198	Fund Name	0.14	2.52	6.30	1.62	0.32	10.88	8.92
199	Fund Name	0.81	1.57	0.97	1.03	0.80	12.66	8.88
200	Fund Name	0.05	1.49	5.05	1.66	0.21	10.75	8.87
201	Fund Name	0.90	1.34	0.17	0.24	0.92	7.97	8.86
202	Fund Name	0.13	2.78	7.39	1.79	0.30	11.21	8.86
203	Fund Name	0.69	0.95	1.97	1.54	0.76	10.97	8.86
204	Fund Name	0.17	2.52	6.81	2.05	0.30	6.49	8.84
205	Fund Name	0.11	2.20	6.09	1.72	0.17	10.90	8.83
206	Fund Name	0.86	0.82	-0.19	0.81	1.40	12.24	8.83
207	Fund Name	0.71	1.08	0.54	0.92	0.75	10.49	8.83
208	Fund Name	0.88	0.87	1.01	0.38	0.74	10.33	8.82
209	Fund Name	0.86	0.82	-0.19	0.81	1.52	12.24	8.82
210	Fund Name	0.79	0.75	0.52	0.93	1.00	12.90	8.81
211	Fund Name	0.08	1.92	5.74	1.66	0.32	10.58	8.81
212	Fund Name	0.04	1.48	5.24	1.53	0.76	10.55	8.80
213	Fund Name	0.88	0.89	-1.26	0.59	0.79	10.06	8.79
214	Fund Name	0.89	0.63	0.50	1.01	0.25	10.61	8.78
215	Fund Name	0.89	0.85	-1.28	0.58	0.48	9.09	8.77
216	Fund Name	0.11	2.37	6.20	1.60	0.80	10.73	8.77
217	Fund Name	0.12	2.01	5.55	1.77	0.34	10.30	8.74
218	Fund Name	0.69	1.23	0.99	1.02	1.09	13.16	8.72
219	Fund Name	0.93	0.87	-0.48	0.77	0.27	10.97	8.70
220	Fund Name	0.13	2.24	6.24	1.93	0.62	9.53	8.68
221	Fund Name	0.02	1.11	4.24	1.21	0.81	10.51	8.68
222	Fund Name	0.09	1.71	5.41	1.90	0.28	10.26	8.67
223	Fund Name	0.54	0.97	1.35	1.12	0.52	10.85	8.66
224	Fund Name	0.74	1.64	0.10	0.76	0.25	11.18	8.65
225	Fund Name	0.09	1.55	5.44	2.26	0.28	9.23	8.64
226	Fund Name	0.06	1.44	4.74	1.71	0.34	10.19	8.64
227	Fund Name	0.03	0.96	4.40	1.81	0.22	11.71	8.62
228	Fund Name	0.13	2.79	7.11	1.68	0.65	10.82	8.61
229	Fund Name	0.10	1.89	5.21	1.65	0.30	9.99	8.60
230	Fund Name	0.83	1.43	-0.02	0.77	0.88	10.24	8.59
231	Fund Name	0.13	2.50	5.98	1.50	0.54	10.58	8.59
232	Fund Name	0.71	1.63	1.57	1.11	0.63	13.25	8.59
233	Fund Name	0.83	1.36	0.42	0.91	1.76	9.20	8.59
234	Fund Name	0.17	2.67	6.75	1.86	0.75	5.98	8.59
235	Fund Name	0.92	0.75	-0.11	0.85	1.08	10.51	8.57
236	Fund Name	0.06	1.23	4.25	1.81	0.42	9.74	8.57
237	Fund Name	0.13	2.57	6.26	1.54	0.50	9.27	8.57
238	Fund Name	0.85	1.78	0.21	0.84	1.97	11.53	8.57
239	Fund Name	0.51	1.35	1.24	0.93	1.16	12.66	8.56
240	Fund Name	0.61	1.13	1.27	1.08	1.13	11.87	8.56
241	Fund Name	0.83	0.54	0.11	0.87	0.44	10.71	8.55
242	Fund Name	0.02	1.04	3.76	1.21	0.83	9.78	8.55
243	Fund Name	0.86	1.76	0.29	0.86	1.76	10.72	8.55
244	Fund Name	0.62	0.77	1.84	1.57	0.35	10.38	8.54
245	Fund Name	0.80	1.23	0.33	0.88	0.51	10.39	8.53
246	Fund Name	0.48	1.05	1.82	1.17	0.40	9.25	8.53
247	Fund Name	0.02	0.83	3.93	1.56	1.16	10.66	8.52
248	Fund Name	0.17	2.22	5.83	2.01	0.25	10.10	8.52
249	Fund Name	0.07	0.80	3.96	3.06	0.19	8.85	8.51
250	Fund Name	0.84	1.38	0.64	0.98	1.62	10.24	8.48
251	Fund Name	0.01	0.91	4.18	1.31	0.35	11.17	8.46
252	Fund Name	0.07	1.76	5.23	1.61	0.40	10.19	8.43
253	Fund Name	0.04	1.26	5.05	1.80	0.81	10.39	8.43
254	Fund Name	0.78	1.64	0.30	0.83	0.89	12.34	8.39
255	Fund Name	0.11	2.20	5.69	1.54	0.55	10.47	8.38
256	Fund Name	0.05	1.49	4.63	1.46	0.61	10.31	8.37
257	Fund Name	0.24	0.78	0.71	0.63	0.45	10.43	8.37
258	Fund Name	0.63	1.02	0.63	0.91	0.16	10.54	8.33
259	Fund Name	0.82	0.82	-0.27	0.09	0.34	9.33	8.31
260	Fund Name	0.04	1.13	4.40	1.81	1.01	10.25	8.30
261	Fund Name	0.08	1.92	5.23	1.43	0.78	10.06	8.27
262	Fund Name	0.06	0.79	3.72	2.82	0.36	8.64	8.26
263	Fund Name	0.11	0.93	3.99	3.33	0.30	7.90	8.16
264	Fund Name	0.69	0.94	1.31	1.26	1.44	10.23	8.16
265	Fund Name	0.02	1.00	4.95	1.63	0.23	10.13	8.16
266	Fund Name	0.63	1.21	1.17	1.04	0.23	7.54	8.15
267	Fund Name	0.03	0.94	3.96	1.58	0.57	11.29	8.15
268	Fund Name	0.11	2.01	5.00	1.48	0.84	9.75	8.15
269	Fund Name	0.06	1.41	4.53	1.66	1.14	9.95	8.12
270	Fund Name	0.09	1.72	4.91	1.63	0.80	9.69	8.11
271	Fund Name	0.83	0.54	-0.28	0.74	0.90	10.23	8.10
272	Fund Name	0.80	1.36	0.35	0.87	1.88	10.05	8.03
273	Fund Name	0.11	1.05	3.90	2.75	0.32	7.71	8.03
274	Fund Name	0.80	0.80	10.84	-0.33	1.15	-2.24	8.01
275	Fund Name	0.96	0.90	4.02	0.53	1.84	63.60	8.00
276	Fund Name	0.10	1.17	3.98	2.32	0.21	8.36	7.99
277	Fund Name	0.80	0.80	-0.09	0.19	0.66	10.94	7.99
278	Fund Name	0.17	2.21	5.33	1.72	0.75	9.56	7.98
279	Fund Name	0.09	1.55	4.87	1.92	0.83	8.65	7.97
280	Fund Name	0.87	1.45	0.16	0.85	0.18	9.94	7.96
281	Fund Name	0.14	1.71	3.86	1.37	0.13	8.16	7.95
282	Fund Name	0.73	1.63	-0.54	0.59	0.68	10.57	7.95
283	Fund Name	0.85	1.54	0.06	0.80	0.95	9.43	7.92
284	Fund Name	0.17	1.13	3.72	2.83	0.28	7.40	7.92
285	Fund Name	0.37	1.17	3.36	3.39	0.24	6.05	7.88
286	Fund Name	0.90	1.66	0.08	0.83	1.23	9.84	7.87
287	Fund Name	0.48	1.05	1.31	1.00	0.90	8.70	7.87
288	Fund Name	0.81	1.57	-0.01	0.76	1.54	11.46	7.86
289	Fund Name	0.19	1.08	3.82	3.27	0.40	7.62	7.83
290	Fund Name	0.29	0.98	3.37	3.97	0.23	6.62	7.82
291	Fund Name	0.85	1.46	0.29	0.87	1.28	11.15	7.79
292	Fund Name	0.62	0.77	1.13	1.23	1.02	9.62	7.78
293	Fund Name	0.06	1.22	3.54	1.38	1.02	9.04	7.78
294	Fund Name	0.01	0.85	3.35	1.00	1.05	10.35	7.77
295	Fund Name	0.10	1.88	4.47	1.28	0.93	9.29	7.77
296	Fund Name	0.40	1.37	3.86	3.39	0.13	6.49	7.77
297	Fund Name	0.42	1.11	3.08	3.43	0.33	5.52	7.76
298	Fund Name	0.19	2.60	5.33	1.32	0.23	7.96	7.75
299	Fund Name	0.17	1.13	3.50	2.59	0.51	7.16	7.72
300	Fund Name	0.54	1.41	3.52	3.22	0.11	6.00	7.72
301	Fund Name	0.11	0.92	3.59	2.88	0.61	7.57	7.70
302	Fund Name	0.02	0.99	4.51	1.45	0.65	9.61	7.69
303	Fund Name	0.33	1.08	3.45	3.79	0.32	6.62	7.68
304	Fund Name	0.19	2.60	5.20	1.25	0.36	7.82	7.66
305	Fund Name	0.12	1.06	3.60	2.45	0.65	7.38	7.65
306	Fund Name	0.69	1.24	-0.08	0.68	1.94	12.21	7.64
307	Fund Name	0.25	0.93	3.58	4.35	0.21	7.05	7.63
308	Fund Name	0.22	1.14	3.42	2.83	0.30	6.87	7.62
309	Fund Name	0.45	1.35	3.51	3.15	0.23	6.12	7.59
310	Fund Name	0.88	0.92	0.56	-0.03	0.98	1.09	7.57
311	Fund Name	0.22	1.18	3.58	2.87	1.10	6.96	7.56
312	Fund Name	0.42	1.10	2.86	3.06	0.58	5.27	7.54
313	Fund Name	0.40	1.37	3.68	3.13	0.28	6.33	7.53
314	Fund Name	0.02	1.36	3.08	0.50	0.28	10.84	7.53
315	Fund Name	0.25	0.93	3.46	4.15	0.34	6.92	7.51
316	Fund Name	0.27	1.02	3.56	3.90	0.21	7.00	7.50
317	Fund Name	0.27	0.85	3.24	4.39	0.17	6.43	7.45
318	Fund Name	0.39	1.03	3.46	4.42	0.15	6.38	7.44
319	Fund Name	0.32	0.92	3.33	4.46	0.31	6.41	7.44
320	Fund Name	0.24	0.86	3.26	4.06	0.21	6.65	7.43
321	Fund Name	0.23	1.14	3.20	2.55	0.55	6.61	7.40
322	Fund Name	0.95	0.92	4.30	-0.11	0.68	10.83	7.40
323	Fund Name	0.37	1.18	2.84	2.51	0.89	5.40	7.39
324	Fund Name	0.63	1.20	0.54	0.85	0.98	6.74	7.36
325	Fund Name	0.87	1.44	-0.47	0.65	1.08	9.21	7.34
326	Fund Name	0.39	1.03	3.36	4.24	0.25	6.27	7.33
327	Fund Name	0.27	0.84	3.12	4.19	0.27	6.32	7.33
328	Fund Name	0.24	0.86	3.14	3.85	0.33	6.52	7.32
329	Fund Name	0.50	1.06	3.29	4.45	0.22	6.07	7.32
330	Fund Name	0.32	0.92	3.19	4.19	0.49	6.23	7.31
331	Fund Name	0.27	1.01	3.36	3.61	0.35	6.81	7.29
332	Fund Name	0.33	1.08	3.06	3.14	0.76	6.15	7.28
333	Fund Name	0.50	1.07	3.23	4.30	0.32	5.97	7.26
334	Fund Name	0.85	1.46	0.01	0.79	1.49	10.83	7.26
335	Fund Name	0.44	1.34	3.18	2.68	0.39	5.82	7.24
336	Fund Name	0.10	1.16	3.21	1.68	1.00	7.47	7.23
337	Fund Name	0.55	1.44	3.12	2.48	0.66	5.46	7.22
338	Fund Name	0.30	1.14	2.80	2.31	0.20	6.13	7.19
339	Fund Name	0.05	0.82	2.70	1.46	0.26	7.03	7.15
340	Fund Name	0.30	0.98	2.73	2.89	0.83	6.00	7.11
341	Fund Name	0.34	0.85	2.47	3.29	0.11	4.93	7.02
342	Fund Name	0.29	1.38	3.60	2.52	0.23	6.19	6.99
343	Fund Name	0.26	0.95	2.37	2.26	0.69	4.89	6.99
344	Fund Name	0.22	1.31	2.82	1.57	0.29	5.77	6.97
345	Fund Name	0.96	0.90	3.02	0.48	2.79	62.12	6.97
346	Fund Name	0.34	0.87	2.36	2.97	0.21	4.84	6.94
347	Fund Name	0.43	0.85	2.25	3.19	0.10	4.77	6.80
348	Fund Name	0.86	0.88	3.08	-0.51	0.86	-9.06	6.77
349	Fund Name	0.42	0.81	2.15	3.18	0.21	4.71	6.76
350	Fund Name	0.41	0.89	2.19	2.73	0.22	4.55	6.76
351	Fund Name	0.47	1.08	-0.40	0.46	0.76	10.93	6.76
352	Fund Name	0.44	0.80	2.19	3.40	0.13	4.87	6.76
353	Fund Name	0.44	0.85	2.18	3.10	0.20	4.67	6.75
354	Fund Name	0.44	0.85	2.15	2.98	0.18	4.66	6.73
355	Fund Name	0.28	1.38	3.35	2.25	0.46	5.97	6.73
356	Fund Name	0.43	0.85	2.19	3.01	0.19	4.69	6.73
357	Fund Name	0.44	0.83	2.12	3.03	0.11	4.73	6.72
358	Fund Name	0.47	0.87	2.18	3.03	0.21	4.74	6.72
359	Fund Name	0.44	0.84	2.12	3.00	0.20	4.70	6.70
360	Fund Name	0.40	0.85	2.14	2.83	0.08	4.55	6.69
361	Fund Name	0.39	0.85	1.99	2.46	0.12	4.30	6.69
362	Fund Name	0.35	0.78	1.97	2.64	0.15	4.35	6.69
363	Fund Name	0.41	0.82	2.08	2.91	0.17	4.58	6.69
364	Fund Name	0.43	0.87	2.11	2.74	0.15	4.54	6.68
365	Fund Name	0.95	0.92	0.20	-0.25	1.09	16.09	6.68
366	Fund Name	0.40	0.81	2.05	2.89	0.17	4.57	6.68
367	Fund Name	0.42	0.81	2.06	2.94	0.31	4.61	6.67
368	Fund Name	0.40	0.81	2.04	2.78	0.15	4.57	6.67
369	Fund Name	0.44	0.86	2.10	2.83	0.25	4.59	6.66
370	Fund Name	0.39	0.82	2.02	2.68	0.12	4.48	6.66
371	Fund Name	0.45	0.79	2.08	3.24	0.17	4.83	6.66
372	Fund Name	0.44	0.84	2.09	2.87	0.30	4.57	6.66
373	Fund Name	0.37	0.78	2.00	2.84	0.28	4.50	6.66
374	Fund Name	0.41	0.89	2.09	2.50	0.32	4.45	6.65
375	Fund Name	0.38	0.79	1.97	2.68	0.15	4.45	6.65
376	Fund Name	0.46	0.88	2.10	2.78	0.32	4.62	6.64
377	Fund Name	0.19	1.02	2.45	1.80	0.40	5.19	6.62
378	Fund Name	0.44	0.84	2.04	2.77	0.32	4.58	6.62
379	Fund Name	0.41	0.81	2.00	2.79	0.18	4.57	6.62
380	Fund Name	0.41	0.82	2.01	2.72	0.24	4.48	6.62
381	Fund Name	0.43	0.83	2.00	2.70	0.20	4.51	6.61
382	Fund Name	0.40	0.81	1.98	2.65	0.20	4.52	6.61
383	Fund Name	0.35	0.78	1.89	2.46	0.14	4.26	6.60
384	Fund Name	0.28	0.78	1.77	1.96	0.15	3.97	6.59
385	Fund Name	0.36	0.77	1.99	2.83	0.11	4.57	6.59
386	Fund Name	0.40	0.81	1.98	2.68	0.26	4.48	6.59
387	Fund Name	0.40	0.84	2.01	2.56	0.18	4.44	6.58
388	Fund Name	0.39	0.85	1.89	2.23	0.22	4.19	6.58
389	Fund Name	0.43	0.87	2.01	2.53	0.23	4.45	6.57
390	Fund Name	0.37	0.78	1.86	2.48	0.15	4.38	6.57
391	Fund Name	0.38	0.79	1.89	2.51	0.22	4.37	6.57
392	Fund Name	0.44	0.83	1.98	2.69	0.25	4.59	6.57
393	Fund Name	0.40	0.82	1.93	2.48	0.21	4.39	6.56
394	Fund Name	0.43	0.85	2.20	3.06	0.11	4.69	6.56
395	Fund Name	0.41	0.81	1.92	2.60	0.26	4.48	6.54
396	Fund Name	0.13	0.90	2.17	1.51	0.31	4.75	6.53
397	Fund Name	0.43	0.83	1.90	2.45	0.30	4.41	6.51
398	Fund Name	0.31	1.16	2.12	1.30	0.97	5.31	6.50
399	Fund Name	0.28	0.77	1.66	1.80	0.20	3.92	6.49
400	Fund Name	0.38	0.78	1.80	2.34	0.20	4.32	6.49
401	Fund Name	0.37	0.78	1.91	2.60	0.21	4.47	6.47
402	Fund Name	0.42	0.87	2.04	2.54	0.36	4.42	6.41
403	Fund Name	0.04	0.80	2.03	0.93	0.88	6.40	6.40
404	Fund Name	0.22	1.30	2.08	0.75	1.01	5.03	6.20
405	Fund Name	0.10	0.81	1.48	0.75	0.42	3.76	6.19
406	Fund Name	0.13	0.94	1.90	1.06	0.45	3.94	6.09
407	Fund Name	0.19	1.02	1.76	0.88	1.10	4.42	5.92
408	Fund Name	0.93	0.89	1.85	0.42	1.14	58.14	5.74
409	Fund Name	0.13	0.90	1.41	0.56	1.06	3.98	5.70
410	Fund Name	0.84	0.82	7.88	-0.28	1.09	4.25	5.06
411	Fund Name	0.91	0.86	1.26	0.20	1.07	9.43	NA
412	Fund Name	1.00	1.00	0.99	0.11	0.15	8.17	NA
413	Fund Name	0.92	0.78	2.13	0.27	0.77	9.75	NA
414	Fund Name	0.90	0.82	1.46	0.14	0.28	9.21	NA
415	Fund Name	1.00	1.01	1.02	0.12	0.05	8.17	NA
416	Fund Name	0.99	1.00	2.91	0.21	0.05	9.39	NA
417	Fund Name	0.99	0.98	2.35	0.18	0.30	9.57	NA
418	Fund Name	0.99	0.98	2.59	0.19	0.10	9.81	NA
419	Fund Name	1.00	0.99	0.99	0.11	0.06	8.37	NA
420	Fund Name	0.99	0.98	2.83	0.20	0.22	9.40	NA
421	Fund Name	1.00	0.99	-0.20	0.06	0.26	7.61	NA
422	Fund Name	1.00	1.01	1.07	0.12	0.10	8.41	NA
423	Fund Name	0.99	1.00	2.99	0.21	0.10	9.50	NA
424	Fund Name	0.96	0.93	0.88	0.06	0.86	12.24	NA
425	Fund Name	0.67	1.22	2.11	1.38	0.49	11.40	NA
426	Fund Name	0.98	1.01	4.86	0.24	0.36	16.30	NA
427	Fund Name	0.92	0.86	-0.17	0.84	0.10	11.00	NA
428	Fund Name	0.87	0.97	0.41	0.03	0.88	15.36	NA
429	Fund Name	0.85	1.06	3.62	0.16	0.88	16.81	NA
430	Fund Name	0.89	0.81	2.03	0.05	1.08	0.63	NA
431	Fund Name	0.93	0.97	-0.67	0.96	1.11	40.30	NA
432	Fund Name	0.94	0.81	6.49	0.67	1.20	55.36	NA
433	Fund Name	0.94	0.81	4.83	0.58	2.65	53.01	NA

pandoc.header(colFmt("1C: MF's filtered on Return and Holdings", 'blue'), 1, 'setext')

1C: MF’s filtered on Return and Holdings

top.mf <- aa.mf[, c(1,7,20,22,24,44)]
top.mf <- top.mf[order(top.mf, decreasing = TRUE),]
top.mf$aax <- top.mf$`10 Yr Ret (%)`
top.mf <- top.mf[1:15,]

rownames(top.mf) <- NULL
value.string <- paste("Top 15 MF's with highest 10 Year Return ")
row.ctr <- nrow(top.mf)
paste(colFmt(value.string, "blue"))

[1] “Top 15 MF’s with highest 10 Year Return ”

top.mf[1:row.ctr,] %>%
  mutate(
    Ser.No = row.names(.),
    Fund = (`Fund Name`),
    Return_1_Yr = color_tile("white", "orange")(`1 Yr Ret (%).x`),
    Return_3_Yr = color_tile("white", "green")(`3 Yr Ret (%)`),
    Return_5_Yr = color_tile("white", "blue")(`5 Yr Ret (%)`),
    Return_Ten_Yr = color_tile("white", "red")(aax),
    NAV = color_tile("white", "purple")('Net Assets (Cr).y')
    
  ) %>%
  select(Ser.No,Fund, Return_1_Yr, Return_3_Yr,Return_5_Yr,Return_Ten_Yr, NAV) %>%
  kable(escape = F) %>%
  kable_styling("hover", full_width = T) %>%
  scroll_box(width = "100%", height = "300px")

Ser.No	Fund	Return_1_Yr	Return_3_Yr	Return_5_Yr	Return_Ten_Yr	NAV
1	UTI Value Opportunities Fund - Regular Plan	12.71	6.68	9.17	9.23	Net Assets (Cr).y
2	UTI Value Opportunities Fund - Direct Plan	13.44	7.42	9.95	NA	Net Assets (Cr).y
3	UTI Unit Linked Insurance Plan - Direct Plan	10.67	4.90	7.66	NA	Net Assets (Cr).y
4	UTI Unit Linked Insurance Plan	9.85	4.24	7.00	7.73	Net Assets (Cr).y
5	UTI Ultra Short Term Fund - Regular Plan	5.49	5.18	6.25	7.55	Net Assets (Cr).y
6	UTI Ultra Short Term Fund - Direct	6.07	5.78	6.86	NA	Net Assets (Cr).y
7	UTI Treasury Advantage Fund - Regular Plan	7.57	3.35	5.23	7.26	Net Assets (Cr).y
8	UTI Treasury Advantage Fund - Direct Plan	7.66	3.48	5.37	NA	Net Assets (Cr).y
9	UTI Transportation and Logistics Fund - Regular Plan	2.36	-7.10	1.74	11.90	Net Assets (Cr).y
10	UTI Transportation and Logistics Fund - Direct Plan	3.44	-6.06	2.92	NA	Net Assets (Cr).y
11	UTI Short Term Income Fund - Regular Plan	10.45	3.76	5.59	7.79	Net Assets (Cr).y
12	UTI Short Term Income Fund - Direct Plan	10.93	4.24	6.09	NA	Net Assets (Cr).y
13	UTI Sensex Exchange Traded Fund	9.48	10.78	12.50	NA	Net Assets (Cr).y
14	UTI Retirement Benefit Pension Fund - Regular Plan	9.27	2.25	6.49	7.15	Net Assets (Cr).y
15	UTI Retirement Benefit Pension Fund - Direct Plan	10.04	2.87	7.15	NA	Net Assets (Cr).y

top.mf <- aa.mf[, c(1,7,20,22,24,44)]
top.mf <- top.mf[order(top.mf$`5 Yr Ret (%)`, decreasing = TRUE),]
top.mf$aax <- top.mf$`10 Yr Ret (%)`
top.mf <- top.mf[1:15,]

rownames(top.mf) <- NULL
value.string <- paste("Top 15 MF's with highest 5 Year Return ")
row.ctr <- nrow(top.mf)
paste(colFmt(value.string, "blue"))

[1] “Top 15 MF’s with highest 5 Year Return ”

top.mf[1:row.ctr,] %>%
  mutate(
    Ser.No = row.names(.),
    Fund = (`Fund Name`),
    Return_1_Yr = color_tile("white", "orange")(`1 Yr Ret (%).x`),
    Return_3_Yr = color_tile("white", "green")(`3 Yr Ret (%)`),
    Return_5_Yr = color_tile("white", "blue")(`5 Yr Ret (%)`),
    Return_Ten_Yr = color_tile("white", "red")(aax),
    NAV = color_tile("white", "purple")('Net Assets (Cr).y')
    
  ) %>%
  select(Ser.No,Fund, Return_1_Yr, Return_3_Yr,Return_5_Yr,Return_Ten_Yr, NAV) %>%
  kable(escape = F) %>%
  kable_styling("hover", full_width = T) %>%
  scroll_box(width = "100%", height = "300px")

Ser.No	Fund	Return_1_Yr	Return_3_Yr	Return_5_Yr	Return_Ten_Yr	NAV
1	SBI Tax Advantage Fund - Series III - Direct Plan	29.97	15.87	18.04	NA	Net Assets (Cr).y
2	SBI Tax Advantage Fund - Series II	27.17	11.23	17.78	NA	Net Assets (Cr).y
3	Aditya Birla Sun Life Digital India Fund - Direct Plan	47.09	25.52	17.61	NA	Net Assets (Cr).y
4	SBI Tax Advantage Fund - Series III - Regular Plan	29.33	15.08	17.50	NA	Net Assets (Cr).y
5	SBI Banking & Financial Services Fund - Direct Plan	0.72	10.46	17.39	NA	Net Assets (Cr).y
6	Mirae Asset Emerging Bluechip Fund - Direct Plan	16.77	9.99	17.25	NA	Net Assets (Cr).y
7	ICICI Prudential Technology Fund - Direct Plan	51.39	26.09	16.72	NA	Net Assets (Cr).y
8	Quant Tax Plan - Direct Plan	25.68	10.59	16.71	NA	Net Assets (Cr).y
9	Aditya Birla Sun Life Digital India Fund	45.67	24.32	16.61	13.83	Net Assets (Cr).y
10	Mirae Asset Emerging Bluechip Fund - Regular Plan	15.62	9.00	16.24	18.61	Net Assets (Cr).y
11	SBI Banking & Financial Services Fund - Regular Plan	-0.42	9.17	16.14	NA	Net Assets (Cr).y
12	Quant Tax Plan	23.44	9.35	15.89	7.85	Net Assets (Cr).y
13	IIFL Focused Equity Fund - Direct Plan	18.68	13.18	15.85	NA	Net Assets (Cr).y
14	Axis Focused 25 Fund - Direct Plan	9.64	11.35	15.81	NA	Net Assets (Cr).y
15	ICICI Prudential Technology Fund	50.48	25.05	15.79	16.67	Net Assets (Cr).y

top.mf <- aa.mf[, c(1,7,20,22,24,44)]
top.mf <- top.mf[order(top.mf$`3 Yr Ret (%)`, decreasing = TRUE),]
top.mf$aax <- top.mf$`10 Yr Ret (%)`
top.mf <- top.mf[1:15,]

rownames(top.mf) <- NULL
value.string <- paste("Top 15 MF's with highest 3 Year Return ")
row.ctr <- nrow(top.mf)
paste(colFmt(value.string, "blue"))

[1] “Top 15 MF’s with highest 3 Year Return ”

top.mf[1:row.ctr,] %>%
  mutate(
    Ser.No = row.names(.),
    Fund = (`Fund Name`),
    Return_1_Yr = color_tile("white", "orange")(`1 Yr Ret (%).x`),
    Return_3_Yr = color_tile("white", "green")(`3 Yr Ret (%)`),
    Return_5_Yr = color_tile("white", "blue")(`5 Yr Ret (%)`),
    Return_Ten_Yr = color_tile("white", "red")(aax),
    NAV = color_tile("white", "purple")('Net Assets (Cr).y')
    
  ) %>%
  select(Ser.No,Fund, Return_1_Yr, Return_3_Yr,Return_5_Yr,Return_Ten_Yr, NAV) %>%
  kable(escape = F) %>%
  kable_styling("hover", full_width = T) %>%
  scroll_box(width = "100%", height = "300px")

Ser.No	Fund	Return_1_Yr	Return_3_Yr	Return_5_Yr	Return_Ten_Yr	NAV
1	Tata Digital India Fund - Direct Plan	40.30	27.15	NA	NA	Net Assets (Cr).y
2	ICICI Prudential Technology Fund - Direct Plan	51.39	26.09	16.72	NA	Net Assets (Cr).y
3	Aditya Birla Sun Life Digital India Fund - Direct Plan	47.09	25.52	17.61	NA	Net Assets (Cr).y
4	ICICI Prudential Technology Fund	50.48	25.05	15.79	16.67	Net Assets (Cr).y
5	Tata Digital India Fund - Regular Plan	38.00	25.02	NA	NA	Net Assets (Cr).y
6	Aditya Birla Sun Life Digital India Fund	45.67	24.32	16.61	13.83	Net Assets (Cr).y
7	SBI Technology Opportunities Fund - Direct Plan	37.09	23.81	14.79	NA	Net Assets (Cr).y
8	SBI Technology Opportunities Fund	35.90	22.51	13.76	14.38	Net Assets (Cr).y
9	Nippon India Pharma Fund - Direct Plan	58.29	20.61	10.56	NA	Net Assets (Cr).y
10	Nippon India Pharma Fund	56.92	19.57	9.59	14.84	Net Assets (Cr).y
11	Tata India Pharma & HealthCare Fund - Direct Plan	55.36	18.91	NA	NA	Net Assets (Cr).y
12	Tata India Pharma & HealthCare Fund - Regular Plan	53.01	16.97	NA	NA	Net Assets (Cr).y
13	UTI Healthcare Fund - Direct Plan	63.60	16.56	8.00	NA	Net Assets (Cr).y
14	SBI Tax Advantage Fund - Series III - Direct Plan	29.97	15.87	18.04	NA	Net Assets (Cr).y
15	UTI Healthcare Fund - Regular Plan	62.12	15.42	6.97	11.97	Net Assets (Cr).y

top.mf <- aa.mf[, c(1,7,20,22,24,44)]
top.mf <- top.mf[order(top.mf$`1 Yr Ret (%).x`, decreasing = TRUE),]
top.mf$aax <- top.mf$`10 Yr Ret (%)`
top.mf <- top.mf[1:15,]

rownames(top.mf) <- NULL
value.string <- paste("Top 15 MF's with highest 1 Year Return ")
row.ctr <- nrow(top.mf)
paste(colFmt(value.string, "blue"))

[1] “Top 15 MF’s with highest 1 Year Return ”

top.mf[1:row.ctr,] %>%
  mutate(
    Ser.No = row.names(.),
    Fund = (`Fund Name`),
    Return_1_Yr = color_tile("white", "orange")(`1 Yr Ret (%).x`),
    Return_3_Yr = color_tile("white", "green")(`3 Yr Ret (%)`),
    Return_5_Yr = color_tile("white", "blue")(`5 Yr Ret (%)`),
    Return_Ten_Yr = color_tile("white", "red")(aax),
    NAV = color_tile("white", "purple")('Net Assets (Cr).y')
    
  ) %>%
  select(Ser.No,Fund, Return_1_Yr, Return_3_Yr,Return_5_Yr,Return_Ten_Yr, NAV) %>%
  kable(escape = F) %>%
  kable_styling("hover", full_width = T) %>%
  scroll_box(width = "100%", height = "300px")

Ser.No	Fund	Return_1_Yr	Return_3_Yr	Return_5_Yr	Return_Ten_Yr	NAV
1	UTI Healthcare Fund - Direct Plan	63.60	16.56	8.00	NA	Net Assets (Cr).y
2	UTI Healthcare Fund - Regular Plan	62.12	15.42	6.97	11.97	Net Assets (Cr).y
3	Nippon India Pharma Fund - Direct Plan	58.29	20.61	10.56	NA	Net Assets (Cr).y
4	SBI Healthcare Opportunities Fund - Direct Plan	58.14	14.06	5.74	NA	Net Assets (Cr).y
5	Nippon India Pharma Fund	56.92	19.57	9.59	14.84	Net Assets (Cr).y
6	SBI Healthcare Opportunities Fund	56.39	12.81	4.52	14.53	Net Assets (Cr).y
7	Tata India Pharma & HealthCare Fund - Direct Plan	55.36	18.91	NA	NA	Net Assets (Cr).y
8	Quant Small Cap Fund - Direct Plan	54.88	7.66	7.70	NA	Net Assets (Cr).y
9	Quant Small Cap Fund	54.22	7.23	7.44	7.52	Net Assets (Cr).y
10	Tata India Pharma & HealthCare Fund - Regular Plan	53.01	16.97	NA	NA	Net Assets (Cr).y
11	ICICI Prudential Technology Fund - Direct Plan	51.39	26.09	16.72	NA	Net Assets (Cr).y
12	ICICI Prudential Technology Fund	50.48	25.05	15.79	16.67	Net Assets (Cr).y
13	Aditya Birla Sun Life Digital India Fund - Direct Plan	47.09	25.52	17.61	NA	Net Assets (Cr).y
14	Aditya Birla Sun Life Digital India Fund	45.67	24.32	16.61	13.83	Net Assets (Cr).y
15	Tata Digital India Fund - Direct Plan	40.30	27.15	NA	NA	Net Assets (Cr).y

#print(dfSummary(top.mf[,c(1,29, 27,28,25, 5,14,18)]), max.tbl.height = 300, method = "render", footnote = NA)

knitr::opts_chunk$set(echo = TRUE)
pandoc.header(colFmt("Section-2: Interactive Tables-Debt Funds", 'red'), 1, 'setext')

Section-2: Interactive Tables-Debt Funds

pandoc.header(colFmt("2A: Values Table:- R-Sq, Alpha, Beta, Sharpe Ratio & Exp-Ratio", 'blue'), 1, 'setext')

2A: Values Table:- R-Sq, Alpha, Beta, Sharpe Ratio & Exp-Ratio

disp.df <- vr.df.new[grep("DT-", vr.df.new$Category),c(1,3,4,5,29,27,28,25)]
datatable(disp.df[order(disp.df$Category),], filter = "top", options = list(scrollY = '300px'), rownames = FALSE )

pandoc.header(colFmt("2B: Performance and Ranking Table", 'blue'), 1, 'setext')

2B: Performance and Ranking Table

disp.df <- vr.df.new[grep("DT-", vr.df.new$Category),c(1,3,16,17,18,19,20,21,22,24)]
datatable(disp.df[order(disp.df$`10 Yr Ret (%)`, disp.df$`5 Yr Ret (%)`, decreasing = TRUE),], 
          filter = "top", options = list(scrollY = '300px'), rownames = FALSE )

pandoc.header(colFmt("2C: Turnover and Risks Table", 'blue'), 1, 'setext')

2C: Turnover and Risks Table

disp.df <- vr.df.new[grep("DT-", vr.df.new$Category),c(1,3,4,8,9,23,31,32,33,34)]
datatable(disp.df[order(disp.df$Category),], filter = "top", options = list(scrollY = '300px'), rownames = FALSE )

knitr::opts_chunk$set(echo = TRUE)
pandoc.header(colFmt("Section-3: Interactive Tables-Equity Funds", 'red'), 1, 'setext')

Section-3: Interactive Tables-Equity Funds

pandoc.header(colFmt("3A: Values Table:- R-Sq, Alpha, Beta, Sharpe Ratio & Exp-Ratio", 'blue'), 1, 'setext')

3A: Values Table:- R-Sq, Alpha, Beta, Sharpe Ratio & Exp-Ratio

disp.df <- vr.df.new[grep("EQ-", vr.df.new$Category),c(1,3,4,5,29,27,28,25)]
datatable(disp.df[order(disp.df$Category),], filter = "top", options = list(scrollY = '300px'), rownames = FALSE )

pandoc.header(colFmt("3B: Performance and Ranking Table", 'blue'), 1, 'setext')

3B: Performance and Ranking Table

disp.df <- vr.df.new[grep("EQ-", vr.df.new$Category),c(1,3,16,17,18,19,20,21,22,24)]
datatable(disp.df[order(disp.df$`10 Yr Ret (%)`, disp.df$`5 Yr Ret (%)`, decreasing = TRUE),], 
          filter = "top", options = list(scrollY = '300px'), rownames = FALSE )

pandoc.header(colFmt("3C: Turnover and Risks Table", 'blue'), 1, 'setext')

3C: Turnover and Risks Table

disp.df <- vr.df.new[grep("EQ-", vr.df.new$Category),c(1,3,4,8,9,23,31,32,33,34)]
datatable(disp.df[order(disp.df$Category),], filter = "top", options = list(scrollY = '300px'), rownames = FALSE )

knitr::opts_chunk$set(echo = TRUE)
pandoc.header(colFmt("Section-4: Interactive Tables-Hybrid Funds", 'red'), 1, 'setext')

Section-4: Interactive Tables-Hybrid Funds

pandoc.header(colFmt("4A: Values Table:- R-Sq, Alpha, Beta, Sharpe Ratio & Exp-Ratio", 'blue'), 1, 'setext')

4A: Values Table:- R-Sq, Alpha, Beta, Sharpe Ratio & Exp-Ratio

disp.df <- vr.df.new[grep("HY-", vr.df.new$Category),c(1,3,4,5,29,27,28,25)]
datatable(disp.df[order(disp.df$Category),], filter = "top", options = list(scrollY = '300px'), rownames = FALSE )

pandoc.header(colFmt("4B: Performance and Ranking Table", 'blue'), 1, 'setext')

4B: Performance and Ranking Table

disp.df <- vr.df.new[grep("HY-", vr.df.new$Category),c(1,3,16,17,18,19,20,21,22,24)]
datatable(disp.df[order(disp.df$`10 Yr Ret (%)`, disp.df$`5 Yr Ret (%)`, decreasing = TRUE),], 
          filter = "top", options = list(scrollY = '300px'), rownames = FALSE )

pandoc.header(colFmt("4C: Turnover and Risks Table", 'blue'), 1, 'setext')

4C: Turnover and Risks Table

disp.df <- vr.df.new[grep("HY-", vr.df.new$Category),c(1,3,4,8,9,23,31,32,33,34)]
datatable(disp.df[order(disp.df$Category),], filter = "top", options = list(scrollY = '300px'), rownames = FALSE )