Tips on how to Iterate Over Columns in Pandas DataFrame

You’ll worth refer to plain syntax to iterate over columns in a pandas DataFrame:

for identify, values in df.iteritems():
  print(values)

Refer to examples display how one can worth this syntax in apply with refer to pandas DataFrame:

import pandas as pd

#build DataFrame
df = pd.DataFrame({'issues': [25, 12, 15, 14, 19],
                   'assists': [5, 7, 7, 9, 12],
                   'rebounds': [11, 8, 10, 6, 6]})

#view DataFrame
df

	issues	assists	rebounds
0	25	5	11
1	12	7	8
2	15	7	10
3	14	9	6
4	19	12	6

Instance 1: Iterate Over All Columns in DataFrame

Refer to code presentations how one can iterate over each column in a pandas DataFrame:

for identify, values in df.iteritems():
  print(values)

0    25
1    12
2    15
3    14
4    19
Title: issues, dtype: int64
0     5
1     7
2     7
3     9
4    12
Title: assists, dtype: int64
0    11
1     8
2    10
3     6
4     6
Title: rebounds, dtype: int64

We will be able to additionally worth refer to syntax to iterate over each column and print simply the column names:

for identify, values in df.iteritems():
  print(identify)

issues
assists
rebounds

Instance 2: Iterate Over Particular Columns

Refer to syntax presentations how one can iterate over particular columns in a pandas DataFrame:

for identify, values in df[['points', 'rebounds']].iteritems():
  print(values)

0    25
1    12
2    15
3    14
4    19
Title: issues, dtype: int64
0    11
1     8
2    10
3     6
4     6
Title: rebounds, dtype: int64

We will be able to additionally worth refer to syntax to iterate over a territory of particular columns:

for identify, values in df.iloc[:, 0:2].iteritems():
  print(values)

0    25
1    12
2    15
3    14
4    19
Title: issues, dtype: int64
0     5
1     7
2     7
3     9
4    12
Title: assists, dtype: int64

You’ll in finding your complete documentation for the iteritems() serve as right here.

Backup Assets

Tips on how to Follow a Serve as to Decided on Columns in Pandas
Tips on how to Trade the Sequence of Columns in Pandas
Tips on how to Shed Columns through Index in Pandas