In [1]:

    

import pandas as pd


    

In [2]:

    

df = pd.DataFrame({'A': [1, 2, 3], 'B': [10, 20, 30], 'C': [100, 200, 300]},
                  index=['One', 'Two', 'Three'])
print(df)


    

    




       A   B    C
One    1  10  100
Two    2  20  200
Three  3  30  300

In [3]:

    

print(df.reindex(index=['Two', 'Three', 'One']))


    

    




       A   B    C
Two    2  20  200
Three  3  30  300
One    1  10  100

In [4]:

    

print(df.reindex(columns=['B', 'C', 'A']))


    

    




        B    C  A
One    10  100  1
Two    20  200  2
Three  30  300  3

In [5]:

    

print(df.reindex(index=['Two', 'Three', 'One'], columns=['B', 'C', 'A']))


    

    




        B    C  A
Two    20  200  2
Three  30  300  3
One    10  100  1

In [6]:

    

print(df.reindex(columns=['B', 'A'], index=['Three', 'One']))


    

    




        B  A
Three  30  3
One    10  1

In [7]:

    

print(df.reindex(['Two', 'Three', 'One'], axis=0))


    

    




       A   B    C
Two    2  20  200
Three  3  30  300
One    1  10  100

In [8]:

    

print(df.reindex(['B', 'C', 'A'], axis='columns'))


    

    




        B    C  A
One    10  100  1
Two    20  200  2
Three  30  300  3

In [9]:

    

print(df[['B', 'C', 'A']])


    

    




        B    C  A
One    10  100  1
Two    20  200  2
Three  30  300  3

In [10]:

    

print(df.reindex(columns=['B', 'X', 'C'], index=['Two', 'One', 'Four']))


    

    




         B   X      C
Two   20.0 NaN  200.0
One   10.0 NaN  100.0
Four   NaN NaN    NaN

In [11]:

    

print(df.reindex(columns=['B', 'X', 'C'], index=['Two', 'One', 'Four'],
                 fill_value=0))


    

    




       B  X    C
Two   20  0  200
One   10  0  100
Four   0  0    0

In [12]:

    

df = pd.DataFrame({'A': [1, 2], 'B': [10, 20], 'C': [100, 200]},
                  index=[10, 20])
print(df)


    

    




    A   B    C
10  1  10  100
20  2  20  200

In [13]:

    

print(df.reindex(index=[5, 10, 15, 20, 25]))


    

    




      A     B      C
5   NaN   NaN    NaN
10  1.0  10.0  100.0
15  NaN   NaN    NaN
20  2.0  20.0  200.0
25  NaN   NaN    NaN

In [14]:

    

print(df.reindex(index=[5, 10, 15, 20, 25], method='bfill'))


    

    




      A     B      C
5   1.0  10.0  100.0
10  1.0  10.0  100.0
15  2.0  20.0  200.0
20  2.0  20.0  200.0
25  NaN   NaN    NaN

In [15]:

    

print(df.reindex(index=[5, 10, 15, 20, 25], method='ffill'))


    

    




      A     B      C
5   NaN   NaN    NaN
10  1.0  10.0  100.0
15  1.0  10.0  100.0
20  2.0  20.0  200.0
25  2.0  20.0  200.0

In [16]:

    

print(df.reindex(index=[5, 10, 15, 20, 25], method='nearest'))


    

    




    A   B    C
5   1  10  100
10  1  10  100
15  2  20  200
20  2  20  200
25  2  20  200

In [17]:

    

print(df.reindex(index=[10, 12, 14, 16, 18, 20]))


    

    




      A     B      C
10  1.0  10.0  100.0
12  NaN   NaN    NaN
14  NaN   NaN    NaN
16  NaN   NaN    NaN
18  NaN   NaN    NaN
20  2.0  20.0  200.0

In [18]:

    

print(df.reindex(index=[10, 12, 14, 16, 18, 20], method='bfill', limit=2))


    

    




      A     B      C
10  1.0  10.0  100.0
12  NaN   NaN    NaN
14  NaN   NaN    NaN
16  2.0  20.0  200.0
18  2.0  20.0  200.0
20  2.0  20.0  200.0

In [19]:

    

print(df.reindex(index=[25, 5, 15], method='bfill'))


    

    




      A     B      C
25  NaN   NaN    NaN
5   1.0  10.0  100.0
15  2.0  20.0  200.0

In [20]:

    

print(df.reindex(index=[5, 15, 25], method='bfill'))


    

    




      A     B      C
5   1.0  10.0  100.0
15  2.0  20.0  200.0
25  NaN   NaN    NaN

In [21]:

    

print(df.reindex(index=[5, 10, 15, 20, 25]).fillna(method='bfill'))


    

    




      A     B      C
5   1.0  10.0  100.0
10  1.0  10.0  100.0
15  2.0  20.0  200.0
20  2.0  20.0  200.0
25  NaN   NaN    NaN

In [22]:

    

print(df.reindex(index=[5, 10, 15, 20, 25]).interpolate())


    

    




      A     B      C
5   NaN   NaN    NaN
10  1.0  10.0  100.0
15  1.5  15.0  150.0
20  2.0  20.0  200.0
25  2.0  20.0  200.0

In [23]:

    

print(df.reindex(columns=['A', 'X', 'C'], method='bfill'))


    

    




    A   X    C
10  1 NaN  100
20  2 NaN  200

In [24]:

    

print(df.reindex(columns=['A', 'X', 'C']).fillna(method='bfill', axis=1))


    

    




      A      X      C
10  1.0  100.0  100.0
20  2.0  200.0  200.0

In [25]:

    

print(df.reindex(columns=['A', 'X', 'C']).interpolate(axis=1))


    

    




      A      X      C
10  1.0   50.5  100.0
20  2.0  101.0  200.0

In [26]:

    

df = pd.DataFrame({'A': [1, 2, 3], 'B': [10, 20, 30], 'C': [100, 200, 300]},
                  index=[20, 10, 30])
print(df)


    

    




    A   B    C
20  1  10  100
10  2  20  200
30  3  30  300

In [27]:

    

# print(df.reindex(index=[10, 15, 20], method='ffill'))
# ValueError: index must be monotonic increasing or decreasing


    

In [28]:

    

print(df.reindex(index=[10, 15, 20]))


    

    




      A     B      C
10  2.0  20.0  200.0
15  NaN   NaN    NaN
20  1.0  10.0  100.0

In [29]:

    

print(df.reindex(index=[10, 15, 20]).fillna(method='bfill'))


    

    




      A     B      C
10  2.0  20.0  200.0
15  1.0  10.0  100.0
20  1.0  10.0  100.0