Pandas DataFrame.replace()

Pandas replace() is a very rich function that is used to replace a string, regex, dictionary, list, and series from the DataFrame. The values of the DataFrame can be replaced with other values dynamically. It is capable of working with the Python regex(regular expression).

It differs from updating with .loc or .iloc, which requires you to specify a location where you want to update with some value.

Syntax:

Parameters:

• to_replace: Defines a pattern that we are trying to replace in dataframe.
• value: It is a value that is used to fill holes in the DataFrame (e.g., 0), alternately a dict of values that specify which value to use for each column (columns not in the dict will not be filled).
  It also allow such objects of regular expressions, strings, and lists or dicts, etc.
• inplace: If it is True, then it replaces in place.

Note: It will also modify any other views on this object (e.g., a column from a DataFrame). Returns the caller if this is True.

• limit: It defines the maximum size gap to forward or backward fill.
• regex: It checks whether to interpret to_replace and/or value as regular expressions. If it is True, then to_replace must be a string. Otherwise, to_replace must be None because this parameter will be interpreted as a regular expression or a list, dict, or array of regular expressions.
• method: It is a method to use for replacement when to_replace is a list.

Returns: It returns a DataFrame object after the replacement.

Example1:

Output

           Language known  Parker        Python  Smith         Android  John          C  William       Android  Dean          Python  Christina     C++  Cornelia      C                     Language known  Parker         1  Smith          4  John           3  William        4  Dean           1  Christina      5  Cornelia       3  

Example2:

The below example replaces a value with another in a DataFrame.

Output

     name       age       City  0Parker      27         US  1Smith       34         Belgium  2John        38         London  

Example3:

The below example replaces the values from a dict:

Output

    name        age     City  0Parker      27       US  1William     29       Belgium  2John        31       London  

Example4:

The below example replaces the values from regex:

Output

    name       age      City  0Parker     27        US  1Ela        34        Belgium  2John       31        London