# Count Values In Pandas Dataframe

### Import the pandas module

import pandas as pd

### Create all the columns of the dataframe as series

year = pd.Series([1875, 1876, 1877, 1878, 1879, 1880, 1881, 1882, 1883, 1884,
1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894])
guardCorps = pd.Series([0,2,2,1,0,0,1,1,0,3,0,2,1,0,0,1,0,1,0,1])
corps1 = pd.Series([0,0,0,2,0,3,0,2,0,0,0,1,1,1,0,2,0,3,1,0])
corps2 = pd.Series([0,0,0,2,0,2,0,0,1,1,0,0,2,1,1,0,0,2,0,0])
corps3 = pd.Series([0,0,0,1,1,1,2,0,2,0,0,0,1,0,1,2,1,0,0,0])
corps4 = pd.Series([0,1,0,1,1,1,1,0,0,0,0,1,0,0,0,0,1,1,0,0])
corps5 = pd.Series([0,0,0,0,2,1,0,0,1,0,0,1,0,1,1,1,1,1,1,0])
corps6 = pd.Series([0,0,1,0,2,0,0,1,2,0,1,1,3,1,1,1,0,3,0,0])
corps7 = pd.Series([1,0,1,0,0,0,1,0,1,1,0,0,2,0,0,2,1,0,2,0])
corps8 = pd.Series([1,0,0,0,1,0,0,1,0,0,0,0,1,0,0,0,1,1,0,1])
corps9 = pd.Series([0,0,0,0,0,2,1,1,1,0,2,1,1,0,1,2,0,1,0,0])
corps10 = pd.Series([0,0,1,1,0,1,0,2,0,2,0,0,0,0,2,1,3,0,1,1])
corps11 = pd.Series([0,0,0,0,2,4,0,1,3,0,1,1,1,1,2,1,3,1,3,1])
corps14 = pd.Series([ 1,1,2,1,1,3,0,4,0,1,0,3,2,1,0,2,1,1,0,0])
corps15 = pd.Series([0,1,0,0,0,0,0,1,0,1,1,0,0,0,2,2,0,0,0,0])

### Create a dictionary variable that assigns variable names

variables = dict(guardCorps = guardCorps, corps1 = corps1,
corps2 = corps2, corps3 = corps3, corps4 = corps4,
corps5 = corps5, corps6 = corps6, corps7 = corps7,
corps8 = corps8, corps9 = corps9, corps10 = corps10,
corps11 = corps11 , corps14 = corps14, corps15 = corps15)

### Create a dataframe and set the order of the columns using the columns attribute

horsekick = pd.DataFrame(variables, columns = ['guardCorps',
'corps1', 'corps2',
'corps3', 'corps4',
'corps5', 'corps6',
'corps7', 'corps8',
'corps9', 'corps10',
'corps11', 'corps14',
'corps15'])

### Set the dataframe’s index to be year

horsekick.index = [1875, 1876, 1877, 1878, 1879, 1880, 1881, 1882, 1883, 1884,
1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894]

### View the horsekick dataframe

horsekick
guardCorps corps1 corps2 corps3 corps4 corps5 corps6 corps7 corps8 corps9 corps10 corps11 corps14 corps15
1875 0 0 0 0 0 0 0 1 1 0 0 0 1 0
1876 2 0 0 0 1 0 0 0 0 0 0 0 1 1
1877 2 0 0 0 0 0 1 1 0 0 1 0 2 0
1878 1 2 2 1 1 0 0 0 0 0 1 0 1 0
1879 0 0 0 1 1 2 2 0 1 0 0 2 1 0
1880 0 3 2 1 1 1 0 0 0 2 1 4 3 0
1881 1 0 0 2 1 0 0 1 0 1 0 0 0 0
1882 1 2 0 0 0 0 1 0 1 1 2 1 4 1
1883 0 0 1 2 0 1 2 1 0 1 0 3 0 0
1884 3 0 1 0 0 0 0 1 0 0 2 0 1 1
1885 0 0 0 0 0 0 1 0 0 2 0 1 0 1
1886 2 1 0 0 1 1 1 0 0 1 0 1 3 0
1887 1 1 2 1 0 0 3 2 1 1 0 1 2 0
1888 0 1 1 0 0 1 1 0 0 0 0 1 1 0
1889 0 0 1 1 0 1 1 0 0 1 2 2 0 2
1890 1 2 0 2 0 1 1 2 0 2 1 1 2 2
1891 0 0 0 1 1 1 0 1 1 0 3 3 1 0
1892 1 3 2 0 1 1 3 0 1 1 0 1 1 0
1893 0 1 0 0 0 1 0 2 0 0 1 3 0 0
1894 1 0 0 0 0 0 0 0 1 0 1 1 0 0

### Count the number of times each number of deaths occurs in each regiment

result = horsekick.apply(pd.value_counts).fillna(0); result
guardCorps corps1 corps2 corps3 corps4 corps5 corps6 corps7 corps8 corps9 corps10 corps11 corps14 corps15
0 9.0 11.0 12.0 11.0 12.0 10.0 9.0 11.0 13.0 10.0 10.0 6 6 14.0
1 7.0 4.0 4.0 6.0 8.0 9.0 7.0 6.0 7.0 7.0 6.0 8 8 4.0
2 3.0 3.0 4.0 3.0 0.0 1.0 2.0 3.0 0.0 3.0 3.0 2 3 2.0
3 1.0 2.0 0.0 0.0 0.0 0.0 2.0 0.0 0.0 0.0 1.0 3 2 0.0
4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1 1 0.0

### Count the number of times each monthly death total appears in guardCorps

pd.value_counts(horsekick['guardCorps'].values, sort=False)
0    9
1    7
2    3
3    1
dtype: int64


### List all the unique values in guardCorps

horsekick['guardCorps'].unique()
array([0, 2, 1, 3])