Pandas: Reindexing

Reindexing

• This functionality is used to create new object with conformed to new index. Following Python code illustrates the concept of reindexing.

Python code

import pandas as pd

data = [30,20,10,40]

x = pd.Series(data, index=["c","b","a","d"], dtype = float)

print(x)

#calling reindex on series

print("‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒")

print("        Reindexing             ")

print("‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒")

y = x.reindex(["a","b","c","d"])

print(y)

Output

In [10]:

c      30.0

b      20.0

a      10.0

d     40.0

dtype: float64

‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒

            Reindexing

‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒‒

a       10.0

b       20.0

c       30.0

d      40.0

dtype: float64

In [11]:

Syntax of reindex method is

  dataframe.reindex(keys, method, copy, level, fill_value, limit, tolerance)

•  keys: The list or string containing row indexes or column labels.

• Method: The default method is None. It specifies the method to use when filling holes in the indexes. The methods are 'backfill', 'bfill', 'pad', 'ffil', 'nearest'

• Copy: This is an optional parameter. The values can be True or False. The default is True. Whether to return a new object (a copy) when all the new indexes are the same as the old.

•  level: The values can be Number or label. This parameter is optional.

•  fill_value : This function specifies the value to use for missing values. The default value is NaN. This is an optional parameter.

• limit: This function specifies the maximum size gap when forward ‒ or backfilling. This is optional parameter, default is None.

• tolerance: This function specifies maximum size (in absolute numeric distance) to fill for inexact matches, When forward ‒ or backfilling,