4.14. DataFrame Sort¶

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

4.14.1. Sort by Index¶

Works with inplace=True
axis=0 - Rows
axis=1 - Columns

4.14.2. Sort Series¶

df.loc['2000-01-01'].sort_index(ascending=True)
# Evening     0.144044
# Midnight    1.454274
# Morning    -0.103219
# Noon        0.410599
# Name: 2000-01-01 00:00:00, dtype: float64

4.14.3. Sort Rows¶

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

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

df.sort_index(ascending=True, axis='rows')
#              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

4.14.4. Sort Columns¶

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

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

4.14.5. Sort Values¶

Works with inplace=True
axis=0 - Rows
axis=1 - Columns

4.14.6. Sorting Rows by Column Value¶

Sorting values by column:

df.sort_values(by='Morning', ascending=True)
#              Morning      Noon   Evening  Midnight
# 2000-01-04 -2.552990  0.653619  0.864436 -0.742165
# 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
# 1999-12-30  1.764052  0.400157  0.978738  2.240893
# 1999-12-31  1.867558 -0.977278  0.950088 -0.151357
# 2000-01-05  2.269755 -1.454366  0.045759 -0.187184

Sorting values by multiple columns (if values are equal in first column, than compare second):

df.sort_values(by=['Morning', 'Evening'], ascending=True)
#              Morning      Noon   Evening  Midnight
# 2000-01-04 -2.552990  0.653619  0.864436 -0.742165
# 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
# 1999-12-30  1.764052  0.400157  0.978738  2.240893
# 1999-12-31  1.867558 -0.977278  0.950088 -0.151357
# 2000-01-05  2.269755 -1.454366  0.045759 -0.187184

4.14.7. Sorting Columns by Row Values¶

Sorting whole DataFrame, according to values by in row (change column order):

df.sort_values(by='2000-01-05', ascending=True, axis='columns')
#                 Noon  Midnight   Evening   Morning
# 1999-12-30  0.400157  2.240893  0.978738  1.764052
# 1999-12-31 -0.977278 -0.151357  0.950088  1.867558
# 2000-01-01  0.410599  1.454274  0.144044 -0.103219
# 2000-01-02  0.121675  0.333674  0.443863  0.761038
# 2000-01-03 -0.205158 -0.854096  0.313068  1.494079
# 2000-01-04  0.653619 -0.742165  0.864436 -2.552990
# 2000-01-05 -1.454366 -0.187184  0.045759  2.269755

df.sort_values(by=['1999-12-31', '2000-01-05'], ascending=False, axis='columns')
#              Morning   Evening  Midnight      Noon
# 1999-12-30  1.764052  0.978738  2.240893  0.400157
# 1999-12-31  1.867558  0.950088 -0.151357 -0.977278
# 2000-01-01 -0.103219  0.144044  1.454274  0.410599
# 2000-01-02  0.761038  0.443863  0.333674  0.121675
# 2000-01-03  1.494079  0.313068 -0.854096 -0.205158
# 2000-01-04 -2.552990  0.864436 -0.742165  0.653619
# 2000-01-05  2.269755  0.045759 -0.187184 -1.454366

4.14.8. Assignments¶

Todo

Create assignments