CODEWITHSUNDEEP
pythonpandas
nikit34
nikit34

Reputation: 41

How to select columns in a dataframe by type

Suppose I have a dataframe with different types. Let there be columns of float, string and int.

  A     B      C

1 car   4.3    302

2 Lena  -1.2   4

3 I     9.1    18

How do I get a column with type 'float'?

while not referring to the column name directly.

Upvotes: 1

Views: 191

Answers (3)

ColinMac
ColinMac

Reputation: 640

You can use List Comprehensions for this:

Here's a sample dataframe:

import pandas as pd

df = pd.DataFrame({'one' : pd.Series([10, 0, 10, 9], index=['a', 'b', 'c', 'd']), //
  'two' : pd.Series([0, 0, 10., 4.6], index=['a', 'b', 'c', 'd']), //
  'three' : pd.Series(['aaa', 'abc', 'def', 'fff'], index=['a', 'b', 'c', 'd'])})

print(df)
"""
   one   two  three
a   10   0.0      5
b    0   0.0     -1
c   10  10.0      7
d    9   4.6     -1
"""

what are my column types?

for col in df.columns:
        print('col : ',col, ' , datatype: ',df[col].dtype)
"""
col:  one  , datatype:  int64
col:  two  , datatype:  float64
col:  three  , datatype:  object
"""

Return columns of type 'float'

print(df[[col for col in df.columns if df[col].dtype == 'float']])
"""
    two
a   0.0
b   0.0
c  10.0
d   4.6
"""

Return multiple column types (float and int64)

print(df[[col for col in df.columns if df[col].dtype in ['float','int64']]])

"""
   one   two
a   10   0.0
b    0   0.0
c   10  10.0
d    9   4.6
"""

Upvotes: 0

René
René

Reputation: 4827

You can try:

df.select_dtypes(float)

or

df.loc[:, df.dtypes == float]

Upvotes: 2

Scott Boston
Scott Boston

Reputation: 153460

Use, select_dtypes:

df.select_dtypes(include='float')

Output:

     B
1  4.3
2 -1.2
3  9.1

Upvotes: 2

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