Creating a Summary Statistical Table from a Data Frame

Creating a summary statistical table from a data frame

Or using what you have already done, you just need to put those summaries into a list and use do.call

df <- structure(list(age = c(19L, 19L, 21L, 21L, 21L, 18L, 19L, 19L, 21L, 17L, 28L, 22L, 19L, 19L, 18L, 18L, 19L, 19L, 18L, 21L, 19L, 31L, 26L, 19L, 18L, 19L, 26L, 20L, 18L), height_seca1 = c(1800L, 1682L, 1765L, 1829L, 1706L, 1607L, 1578L, 1577L, 1666L, 1710L, 1616L, 1648L, 1569L, 1779L, 1773L, 1816L, 1766L, 1745L, 1716L, 1785L, 1850L, 1875L, 1877L, 1836L, 1825L, 1755L, 1658L, 1816L, 1755L), height_chad1 = c(1797L, 1670L, 1765L, 1833L, 1705L, 1606L, 1576L, 1575L, 1665L, 1716L, 1619L, 1644L, 1570L, 1777L, 1772L, 1809L, 1765L, 1741L, 1714L, 1783L, 1854L, 1880L, 1877L, 1837L, 1823L, 1754L, 1658L, 1818L, 1755L), height_DL = c(180L, 167L, 178L, 181L, 170L, 160L, 156L, 156L, 166L, 172L, 161L, 165L, 155L, 177L, 179L, 181L, 178L, 174L, 170L, 179L, 185L, 188L, 186L, 185L, 182L, 174L, 165L, 183L, 175L), weight_alog1 = c(70L, 69L, 80L, 74L, 103L, 76L, 50L, 61L, 52L, 65L, 66L, 58L, 55L, 55L, 70L, 81L, 77L, 76L, 71L, 64L, 71L, 95L, 106L, 100L, 85L, 79L, 69L, 84L, 67L)), class = "data.frame", row.names = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26", "27", "28", "29"))

tmp <- do.call(data.frame, 
           list(mean = apply(df, 2, mean),
                sd = apply(df, 2, sd),
                median = apply(df, 2, median),
                min = apply(df, 2, min),
                max = apply(df, 2, max),
                n = apply(df, 2, length)))
tmp

                   mean        sd median  min  max  n
age            20.41379  3.300619     19   17   31 29
height_seca1 1737.24138 91.919474   1755 1569 1877 29
height_chad1 1736.48276 92.682492   1755 1570 1880 29
height_DL     173.37931  9.685828    175  155  188 29
weight_alog1   73.41379 14.541854     71   50  106 29

or...

data.frame(t(tmp))

             age height_seca1 height_chad1  height_DL weight_alog1
mean   20.413793   1737.24138   1736.48276 173.379310     73.41379
sd      3.300619     91.91947     92.68249   9.685828     14.54185
median 19.000000   1755.00000   1755.00000 175.000000     71.00000
min    17.000000   1569.00000   1570.00000 155.000000     50.00000
max    31.000000   1877.00000   1880.00000 188.000000    106.00000
n      29.000000     29.00000     29.00000  29.000000     29.00000

How to create a summary statistics table for transformed variables in r

You can just call log on the data you want to summarise first.

For example:

Untransformed summary:

> mtcars |> select(hp, drat, wt) |> summary()
       hp             drat             wt       
 Min.   : 52.0   Min.   :2.760   Min.   :1.513  
 1st Qu.: 96.5   1st Qu.:3.080   1st Qu.:2.581  
 Median :123.0   Median :3.695   Median :3.325  
 Mean   :146.7   Mean   :3.597   Mean   :3.217  
 3rd Qu.:180.0   3rd Qu.:3.920   3rd Qu.:3.610  
 Max.   :335.0   Max.   :4.930   Max.   :5.424  

Tranformed:

> mtcars |> select(hp, drat, wt) |> log() |> summary()
       hp             drat             wt        
 Min.   :3.951   Min.   :1.015   Min.   :0.4141  
 1st Qu.:4.570   1st Qu.:1.125   1st Qu.:0.9479  
 Median :4.812   Median :1.307   Median :1.2009  
 Mean   :4.882   Mean   :1.269   Mean   :1.1217  
 3rd Qu.:5.193   3rd Qu.:1.366   3rd Qu.:1.2835  
 Max.   :5.814   Max.   :1.595   Max.   :1.6908  

Create and Export a Summary Statistics Table

You have a tibble and stargazer doesn't support it. If you change it to dataframe it works.

library(stargazer)

data_stuct <- data.frame(data_stuct)

stargazer(data_stuct[c("BNBClose", "BTCClose", "ADAClose", "LINKClose", 
      "DODGEClose")],type="text",title="Summary Statistics", out="table1.txt")

#Summary Statistics
#========================================================================
#Statistic  N    Mean    St. Dev.    Min    Pctl(25)  Pctl(75)     Max   
#------------------------------------------------------------------------
#BNBClose   10   1.568    0.219     1.217     1.411     1.659     1.965  
#BTCClose   10 4,507.324 220.613  4,229.360 4,339.010 4,731.635 4,826.480
#ADAClose   10   0.022    0.002     0.019     0.021     0.022     0.026  
#LINKClose  10   0.408    0.043     0.346     0.385     0.440     0.476  
#DODGEClose 10   0.001   0.00004    0.001     0.001     0.001     0.001  
------------------------------------------------------------------------

How create summary table for every column?

Of coruse, Pandas have a method for that - describe():

df.describe()

Which gives more statistics than you requested. If you are interested only in mean and std, you can do:

df.describe()[['mean', 'std']]

How to create a dataframe of summary statistics?

You can pass a dict of functions to a groupby to perform the stats using agg:

In [154]:

df.groupby('ID')['Variable_1'].agg({'Mean':np.mean, 'SD':np.std})
Out[154]:
      Mean         SD
ID                   
1234  27.5   6.363961
2345  65.0  11.000000
3456  78.0        NaN

Is there a way in R to create summary statistics table from a list of data

We can use transpose from purrr and flatten or unlist the list elements to be a list of 3

library(purrr)
DF2 <- transpose(DF) %>% 
            map(flatten_dbl)

NOTE: DF is the second dataset in the OP's post

Now, we test with table1

table1::table1(~A+B+C, data=DF2, overall = 'List 1')

-output

---

If we need to create a two column table, convert the list of list of vectors to a single data.frame while creating a column with the names of the outer list element

new_DF <- do.call(rbind, Map(cbind, nm1 = names(DF), 
         lapply(DF, as.data.frame)))
row.names(new_DF) <- NULL

table1::table1(~ A + B + C |nm1, data = new_DF)

-output

Create a summary table from my data.frame

You can use the aggregate function on two variables and use sum in the FUN argument.

summaryDf <- aggregate( data = df , cbind(nkill, nwound) ~ country_txt.factor, FUN = sum)

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