How to sort in pandas

Sort a dataframe by a column valuepython

>>> df.sort_values(by=['col1'])
    col1 col2 col3
0   A    2    0
1   A    1    1
2   B    9    9
5   C    4    3
4   D    7    2
3   NaN  8    4

Source: pandas.pydata.org

Df sort values

>>> df.sort_values(by=['col1'], ascending = False)
    col1 col2 col3
0   A    2    0
1   A    1    1
2   B    9    9
5   C    4    3
4   D    7    2
3   NaN  8    4

Source: pandas.pydata.org

Sorting by column in pandas

# Python, Pandas
# Sorting dataframe df on the values of a column col1

# Return sorted array without modifying the original one
df.sort_values(by=["col1"]) 

# Sort the original array permanently
df.sort_values(by=["col1"], inplace = True)

How to sort in pandas

// Single sort 
>>> df.sort_values(by=['col1'],ascending=False)
// ascending => [False(reverse order) & True(default)]
// Multiple Sort
>>> df.sort_values(by=['col1','col2'],ascending=[True,False])
// with apply() 
>>> df[['col1','col2']].apply(sorted,axis=1)
// axis = [1 & 0], 1 = 'columns', 0 = 'index'

Sort by dataframe

DataFrame.sort_values(self, by, axis=0, ascending=True,
                      inplace=False, kind='quicksort',
                      na_position='last',
                      ignore_index=False)

# Example
df.sort_values(by=['ColToSortBy'])

Pandas sort dataframe by column

# Basic syntax:
import pandas as pd
df.sort_values(by=['col1'])

# Note, this does not sort in place unless you add inplace=True
# Note, add ascending=False if you want to sort in decreasing order
# Note, to sort by more than one column, add other column names to the
#	list like by=['col1', 'col2']

Source: pandas.pydata.org

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