4.5. DataFrame Getitem

import pandas as pd
import numpy as np
np.random.seed(0)

df = pd.DataFrame(
    columns = ['Morning', 'Noon', 'Evening', 'Midnight'],
    index = pd.date_range('1999-12-30', periods=7),
    data = np.random.randn(7, 4))

df
#              Morning      Noon   Evening  Midnight
# 1999-12-30  1.764052  0.400157  0.978738  2.240893
# 1999-12-31  1.867558 -0.977278  0.950088 -0.151357
# 2000-01-01 -0.103219  0.410599  0.144044  1.454274
# 2000-01-02  0.761038  0.121675  0.443863  0.333674
# 2000-01-03  1.494079 -0.205158  0.313068 -0.854096
# 2000-01-04 -2.552990  0.653619  0.864436 -0.742165
# 2000-01-05  2.269755 -1.454366  0.045759 -0.187184

4.5.1. Rationale

  • df.at[]

  • df.loc[]

  • df.iat[]

  • df.iloc[]

  • iat and iloc takes int as argument

  • at and loc takes str as argument

4.5.2. Columns

Single Column:

df.Morning
# 1999-12-30    1.764052
# 1999-12-31    1.867558
# 2000-01-01   -0.103219
# 2000-01-02    0.761038
# 2000-01-03    1.494079
# 2000-01-04   -2.552990
# 2000-01-05    2.269755
# Freq: D, Name: Morning, dtype: float64

df['Morning']
# 1999-12-30    1.764052
# 1999-12-31    1.867558
# 2000-01-01   -0.103219
# 2000-01-02    0.761038
# 2000-01-03    1.494079
# 2000-01-04   -2.552990
# 2000-01-05    2.269755
# Freq: D, Name: Morning, dtype: float64

df.loc[:, 'Morning']
# 1999-12-30    1.764052
# 1999-12-31    1.867558
# 2000-01-01   -0.103219
# 2000-01-02    0.761038
# 2000-01-03    1.494079
# 2000-01-04   -2.552990
# 2000-01-05    2.269755
# Freq: D, Name: Morning, dtype: float64

df.iloc[:, 0]
# 1999-12-30    1.764052
# 1999-12-31    1.867558
# 2000-01-01   -0.103219
# 2000-01-02    0.761038
# 2000-01-03    1.494079
# 2000-01-04   -2.552990
# 2000-01-05    2.269755
# Freq: D, Name: Morning, dtype: float64

Multiple columns:

df[['Morning', 'Evening']]
#              Morning   Evening
# 1999-12-30  1.764052  0.978738
# 1999-12-31  1.867558  0.950088
# 2000-01-01 -0.103219  0.144044
# 2000-01-02  0.761038  0.443863
# 2000-01-03  1.494079  0.313068
# 2000-01-04 -2.552990  0.864436
# 2000-01-05  2.269755  0.045759

4.5.3. Rows

df['2000-01-05'] will imply to take column with name 2000-01-05, hence KeyError:

df['2000-01-05']
# Traceback (most recent call last):
# KeyError: '2000-01-05'

df.loc['2000-01-05']
# Morning     2.269755
# Noon       -1.454366
# Evening     0.045759
# Midnight   -0.187184
# Name: 2000-01-05 00:00:00, dtype: float64

df.loc['2000-01']
#              Morning      Noon   Evening  Midnight
# 2000-01-01 -0.103219  0.410599  0.144044  1.454274
# 2000-01-02  0.761038  0.121675  0.443863  0.333674
# 2000-01-03  1.494079 -0.205158  0.313068 -0.854096
# 2000-01-04 -2.552990  0.653619  0.864436 -0.742165
# 2000-01-05  2.269755 -1.454366  0.045759 -0.187184

df.loc['1999']
#              Morning      Noon   Evening  Midnight
# 1999-12-30  1.764052  0.400157  0.978738  2.240893
# 1999-12-31  1.867558 -0.977278  0.950088 -0.151357

4.5.4. Columns by Index

df.iloc[:, 1]
# 1999-12-30    0.400157
# 1999-12-31   -0.977278
# 2000-01-01    0.410599
# 2000-01-02    0.121675
# 2000-01-03   -0.205158
# 2000-01-04    0.653619
# 2000-01-05   -1.454366
# Freq: D, Name: Noon, dtype: float64

df.iloc[:, [1,2]]
#                 Noon   Evening
# 1999-12-30  0.400157  0.978738
# 1999-12-31 -0.977278  0.950088
# 2000-01-01  0.410599  0.144044
# 2000-01-02  0.121675  0.443863
# 2000-01-03 -0.205158  0.313068
# 2000-01-04  0.653619  0.864436
# 2000-01-05 -1.454366  0.045759

4.5.5. Assignments