In this post, I use prowess data to understand and get some perspective of the Indian firms. Not all firms have the complete data. I plan to discuss some of the balance sheet and profit and loss statement variables in some detail.
The data corresponds to all the bse and nse listed firms for the year 2016 firms. We collect data from the standalone section of the financial statements. The units are million INR.
library(dplyr)
library(ggplot2)
library(psych)
library(stargazer)
table1 = table(sign(df$sa_total_assets), useNA = c("always"))
table1 = as.data.frame(table1)
table2 = table(sign(df$sa_sales), useNA = c("always"))
table2 = as.data.frame(table2)
q.sales = quantile(df$sa_sales, probs = seq(0, 1, 0.25), na.rm = TRUE)
q.assets = quantile(df$sa_total_assets, probs = seq(0, 1, 0.25), na.rm = TRUE)
q.sales
## 0% 25% 50% 75% 100%
## 0.10 72.00 704.00 3824.15 4002577.60
q.assets
## 0% 25% 50% 75% 100%
## -33.000 146.900 688.350 4529.375 23615268.900
stargazer(df[c("sa_sales", "sa_total_assets")], type = "html",
digits = 0, style = "aer",
covariate.labels = c("sales","assets"))
| Statistic | N | Mean | St. Dev. | Min | Pctl(25) | Pctl(75) | Max |
| sales | 2,663 | 12,021 | 106,690 | 0 | 72 | 3,824 | 4,002,578 |
| assets | 3,250 | 41,076 | 506,725 | -33 | 147 | 4,529 | 23,615,269 |
qplot(df$sa_total_assets,xlim = c(0,147), geom="histogram")
qplot(df$sa_total_assets,xlim = c(147, 4529), geom="histogram")
qplot(df$sa_total_assets,xlim = c(4529,max(df$sa_total_assets)), geom="histogram")
qplot(df$sa_total_assets, geom="histogram")
qplot(df$sa_sales,xlim = c(0,72), geom="histogram")
qplot(df$sa_sales,xlim = c(72, 3824), geom="histogram")
qplot(df$sa_sales,xlim = c(3842,max(df$sa_sales)), geom="histogram")
qplot(df$sa_sales, geom="histogram")