Word Count Of Single Column In Pandas Dataframe

Here is my attempt at a word count for a single column using group by with pandas : First setup the data : columns = ['col1','col2','col3'] data = np.array([['word1','word2','wor

Solution 1:

If I understand you correctly, I think this is what you're looking for:

print(to_count.groupby('col1')['col1'].count())

Output:

       col1
word1    2
word3    1

Solution 2:

You can apply value_counts() fn to one column of dataframe. Following applies it all columns one by one:

for onecol in to_count:
    print(onecol, ":\n", to_count[onecol].value_counts())

Output:

col1 :word12word31Name:col1,dtype:int64col2 :word51word21word71Name:col2,dtype:int64col3 :word33Name:col3,dtype:int64

Solution 3:

How about this:

Single column:

df['col1'].value_counts()

will return:

word1    2
word3    1

All columns:

df.apply(lambda col: col.value_counts()).fillna(0).astype(int)

will return:

       col1  col2  col3
word1     2     0     0
word2     0     1     0
word3     1     0     3
word5     0     1     0
word7     0     1     0

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Copy & paste example:

from io import StringIO
import pandas as pd

data = """
    col1   col2   col3
0  word1  word2  word3
1  word1  word5  word3
2  word3  word7  word3
"""

df = pd.read_table(StringIO(data), sep='\s+')

print(df['col1'].value_counts())
print(df.apply(lambda col: col.value_counts().astype(int)).fillna(0).astype(int))