In [1]:

    

import pandas as pd


    

In [2]:

    

df = pd.read_csv('data/src/sample_pandas_normal.csv')
print(df)


    

    




      name  age state  point
0    Alice   24    NY     64
1      Bob   42    CA     92
2  Charlie   18    CA     70
3     Dave   68    TX     70
4    Ellen   24    CA     88
5    Frank   30    NY     57

In [3]:

    

print(df.sort_values('name'))


    

    




      name  age state  point
0    Alice   24    NY     64
1      Bob   42    CA     92
2  Charlie   18    CA     70
3     Dave   68    TX     70
4    Ellen   24    CA     88
5    Frank   30    NY     57

In [4]:

    

print(df.sort_values('name', ascending=False))


    

    




      name  age state  point
5    Frank   30    NY     57
4    Ellen   24    CA     88
3     Dave   68    TX     70
2  Charlie   18    CA     70
1      Bob   42    CA     92
0    Alice   24    NY     64

In [5]:

    

l_order = ['Charlie', 'Alice', 'Dave', 'Bob']


    

In [6]:

    

df['order'] = df['name'].apply(lambda x: l_order.index(x) if x in l_order else -1)
print(df)


    

    




      name  age state  point  order
0    Alice   24    NY     64      1
1      Bob   42    CA     92      3
2  Charlie   18    CA     70      0
3     Dave   68    TX     70      2
4    Ellen   24    CA     88     -1
5    Frank   30    NY     57     -1

In [7]:

    

print(df.sort_values('order'))


    

    




      name  age state  point  order
4    Ellen   24    CA     88     -1
5    Frank   30    NY     57     -1
2  Charlie   18    CA     70      0
0    Alice   24    NY     64      1
3     Dave   68    TX     70      2
1      Bob   42    CA     92      3

In [8]:

    

print(df.sort_values('order').reset_index(drop=True).drop(columns='order'))


    

    




      name  age state  point
0    Ellen   24    CA     88
1    Frank   30    NY     57
2  Charlie   18    CA     70
3    Alice   24    NY     64
4     Dave   68    TX     70
5      Bob   42    CA     92

In [9]:

    

d_order = {'Charlie': 0, 'Alice': 1, 'Dave': 2, 'Bob': 3}


    

In [10]:

    

df['order'] = df['name'].map(d_order)
print(df)


    

    




      name  age state  point  order
0    Alice   24    NY     64    1.0
1      Bob   42    CA     92    3.0
2  Charlie   18    CA     70    0.0
3     Dave   68    TX     70    2.0
4    Ellen   24    CA     88    NaN
5    Frank   30    NY     57    NaN

In [11]:

    

print(df.sort_values('order'))


    

    




      name  age state  point  order
2  Charlie   18    CA     70    0.0
0    Alice   24    NY     64    1.0
3     Dave   68    TX     70    2.0
1      Bob   42    CA     92    3.0
4    Ellen   24    CA     88    NaN
5    Frank   30    NY     57    NaN

In [12]:

    

print(df.sort_values('order', na_position='first'))


    

    




      name  age state  point  order
4    Ellen   24    CA     88    NaN
5    Frank   30    NY     57    NaN
2  Charlie   18    CA     70    0.0
0    Alice   24    NY     64    1.0
3     Dave   68    TX     70    2.0
1      Bob   42    CA     92    3.0

In [13]:

    

print(df.sort_values('order', na_position='first').reset_index(drop=True).drop(columns='order'))


    

    




      name  age state  point
0    Ellen   24    CA     88
1    Frank   30    NY     57
2  Charlie   18    CA     70
3    Alice   24    NY     64
4     Dave   68    TX     70
5      Bob   42    CA     92