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    pandas reset_index() - Rest Index on DataFrame

    pandas reset_index() - Rest Index on DataFrame

    DataFrame.reset_index() method is used to reset the index on the pandas DataFrame. This takes level, drop, inplace, col_level, col_fill as parameters and returns DataFrame. When inplace=True is used, it returns None. Use pandas.DataFrame.set_index() to set column as index.

    In this article, I will cover how to reset index on pandas DataFrame with several examples. We are usually required to reset the index post dropping some rows from DataFrame as it creates a gap in the index.

    Key Points –

    <a id="h-1-quick-examples-of-pandas-reset-index"></a>

    1. Quick Examples of Pandas Reset Index

    Below are some quick examples of reset index on DataFrame.

    
# Quick examples of reset index

# Reset index
df2=df.reset_index()

# Reset index with out assigning to column
df.reset_index(inplace=True, drop=True)

# Set index column name
df.index.name = 'custom_index'

# Reset index starting from 1
df.index = np.arange(1, len(df) + 1)

    <a id="h-2-pandas-dataframe-reset-index-syntax"></a>

    2. pandas.DataFrame.reset_index() Syntax

    Following is the syntax of the pandas.DataFrame.reset_index().

    
DataFrame.reset_index(level=None, drop=False, inplace=False, col_level=0, col_fill='')

    Let's create a pandas DataFrame with examples

    
import pandas as pd

# Create DataFrame from dict
df = pd.DataFrame({'Courses':['Spark','PySpark','Java','PHP'],
           'Fee':[20000,20000,15000,10000],
           'Duration':['35days','35days','40days','30days']})

df=df.drop([2])
print(df)

    Yields below output

    
# Output:
   Courses    Fee Duration
0    Spark  20000   35days
1  PySpark  20000   35days
3      PHP  10000   30days

    <a id="h-3-pandas-rest-index-on-dataframe-example"></a>

    3. Pandas Rest Index on DataFrame Example

    Let's use the pandas.DataFrame.reset_index() syntax to reset the DataFrame index. When we reset the index, the old index is added as a column to DataFrame, and a new sequential index is used

    
# Reset index on DataFrame
df2=df.reset_index()
print(df2)

    Yields below output.

    
# Output:
   index  Courses    Fee Duration
0      0    Spark  20000   35days
1      1  PySpark  20000   35days
2      3      PHP  10000   30days

    If you don't want to add the existing index as a column, use drop=True param and also use inplace=True to update the existing DataFrame.

    
# Drop index as column
df.reset_index(inplace=True, drop=True)
print(df)

    Yields below output

    
# Output:
   Courses    Fee Duration
0    Spark  20000   35days
1  PySpark  20000   35days
2      PHP  10000   30days

    <a id="h-4-reset-index-name-on-dataframe"></a>

    4. Reset Index Name on DataFrame

    Now, let's see how to reset an index name on pandas DataFrame. By default, DataFrame creates with index name as 'index'

    
# Set index name
df.index.name = 'custom_index'
print(df)

    Yields below output.

    
# Output:
              Courses    Fee Duration
custom_index                         
0               Spark  20000   35days
1             PySpark  20000   35days
2                 PHP  10000   30days

    <a id="h-5-reset-index-to-start-from-1"></a>

    5. Reset Index to Start from 1

    When you reset the index it assigns a numerical value starting from zero, some times you may need to assign from 1, you can do this as shown in the below example.

    
# Reset index starting from 1
df.index = np.arange(1, len(df) + 1)
print(df)

    Yields below output

    
# Output:
   Courses    Fee Duration
1    Spark  20000   35days
2  PySpark  20000   35days
3      PHP  10000   30days

    <a id="h-complete-example-of-reset-index-on-dataframe"></a>

    Complete Example of Reset Index on DataFrame

    
import pandas as pd
import numpy as np

# Create DataFrame from dict
df = pd.DataFrame({'Courses':['Spark','PySpark','Java','PHP'],
           'Fee':[20000,20000,15000,10000],
           'Duration':['35days','35days','40days','30days']})

df=df.drop([2])
print(df)

# Reset index
df2=df.reset_index()
print(df2)

# Reset index with out assigning to column
df.reset_index(inplace=True, drop=True)
print(df)

# Set index column name
df.index.name = 'custom_index'
print(df)

# Reset index starting from 1
df.index = np.arange(1, len(df) + 1)
print(df)

    <a id="h-faq-on-pandas-reset-index-rest-index-on-dataframe"></a>

    FAQ on pandas reset_index() – Rest Index on DataFrame

    reset_index() resets the index of a DataFrame to the default integer-based index (0, 1, 2, ...). It also moves the current index to a column, unless specified otherwise.

    You can reset the index by calling the reset_index() method on a DataFrame:

    You can reset the index without adding it as a column by using the drop=True parameter in the reset_index() method.

    By default, reset_index() returns a new DataFrame and does not modify the original DataFrame. To modify the original DataFrame, you can use inplace=True.

    reset_index() does not affect the column names, but if you reset the index and add it as a column, the column will be named "index" by default unless you specify a different name.

    If the DataFrame already has a default integer index (0, 1, 2,...), calling reset_index() will add a new column with the existing index values and reset the index back to the default.

    <a id="h-conclusion"></a>

    Conclusion

    In this article, you have learned how to reset the index on DataFrame by using different prams on the reset_index() method.

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    References