PYTHON

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'

pandas series sort

s.sort_values(ascending=True)
1     1.0
2     3.0
4     5.0
3    10.0
0     NaN
dtype: float64

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

df.sort_values(by='col1', ascending=False)
  col1  col2  col3 col4
4    D     7     2    e
5    C     4     3    F
2    B     9     9    c
0    A     2     0    a
1    A     1     1    B
3  NaN     8     4    D

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']

pandas sort

df.sort_values(by='col1', ascending=False, na_position='first')
  col1  col2  col3 col4
3  NaN     8     4    D
4    D     7     2    e
5    C     4     3    F
2    B     9     9    c
0    A     2     0    a
1    A     1     1    B

pandas dataframe sort by column

df.sort_values(by=['col1])

sort dataframe by function

df = pd.DataFrame(['bit_0', 'bit_2', 'bit_5'], columns=['bit'])
df.sort_values('bit' ,key=lambda x: x.str.split("_",expand=True)[1].astype(int))

sort a dataframe

sort_na_first = gapminder.sort_values('lifeExp',na_position='first')