Pandas DataFrame reset_index() Method
Example
Reset the index back to 0, 1, 2:
import pandas as pd
data = {
"name": ["Sally", "Mary",
"John"],
"age": [50, 40, 30],
"qualified": [True, False,
False]
}
idx = ["X", "Y", "Z"]
df = pd.DataFrame(data, index=idx)
newdf = df.reset_index()
print(newdf)
Try it Yourself »
Definition and Usage
The reset_index()
method allows you reset
the index back to the default 0, 1, 2 etc indexes.
By default this method will keep the "old" idexes in a column named "index",
to avoid this, use the drop
parameter.
Syntax
dataframe.reset_index(level, drop, inplace, col_level, col_fill)
Parameters
The parameters are keyword arguments.
Parameter | Value | Description |
---|---|---|
level | Int String List Tuple |
Optional. Specifies the levels to reset. Default resets all levels |
drop | True |
Optional. default False |
inplace | True |
Optional, default False. If True: the operation is done on the current DataFrame. If False: returns a copy where the operation is done. |
col_level | Int String |
Optional, default 0. For multi level columns, specifies on which level to reset the indexes |
col_fill | Object None |
Optional, default ''. For multi level columns, specifies how the other levels are indexed |
Return Value
A DataFrame with the result, or None if the inplace parameter is set to True.
This function does NOT make changes to the original DataFrame object.