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How to prefix the labels of a series object in pandas
Onyejiaku Theophilus ChidaluOverview
The add_prefix() function in pandas is used to prefix the rows of a Series object.
A Series object is a one-dimensional data structure used to hold integers, strings, and other python objects.
Syntax
The add_prefix() function takes the syntax shown below:
DataFrame.add_prefix(str)
Syntax for the add_prefix() function
Parameter value
The add_prefix() function takes a single required parameter value, str, representing the string to be prefixed or added before each label.
Return value
The add_prefix() function returns a new dataframe with prefixed columns.
Example
# A code to illustrate the add_prefix() function in Pandas
# imporing the pandas library
import pandas as pd
# creating a dataframe
df = pd.Series([10, 20, 30, 40, 50])
print(df)
# adding prefixes to the columns of the dataframe
print(df.add_prefix("row_"))Implementing the add_prefix() function
Explanation
- Line 4: We import the pandas library.
- Line 7: We create a dataframe called
df. - Line 9: We print the
df. - Line 12: We add the prefix
row_to the row labels of thedf. We print the result to the console.
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