Pandas DataFrame sort_index() Method
Example
Sort the DataFrame by index labels:
import pandas as pd
data = {
"age": [50, 40, 30, 40, 20,
10, 30],
"qualified": [True, False, False, False, False, True,
True]
}
idx = ["Mary", "Sally", "Emil", "Tobias", "Linus", "John",
"Peter"]
df = pd.DataFrame(data, index = idx)
newdf =
df.sort_index()
Try it Yourself »
Definition and Usage
The sort_index()
method sorts the DataFrame
by the index.
Syntax
dataframe.sort_index(axis, level, ascending, inplace, kind,
na_position, sort_remaining, ignore_index, key)
Parameters
The parameters are keyword arguments.
Parameter | Value | Description |
---|---|---|
axis | 0 |
Optional. Default 0. Specifies the axis to sort by |
level | String Number List of Strings/Numbers |
Optional. Default None. Specifies the index level to sort on |
ascending | True |
Optional, default True. Specifies whether to sort ascending (0 -> 9) or descending (9 -> 0) |
inplace | True |
Optional, default False. Specifies whether to perform the operation on the original DataFrame or not, if not, which is default, this method returns a new DataFrame |
kind | 'quicksort' |
Optional, default 'quicksort'. Specifies the sorting algorithm |
na_position | 'first' |
Optional, default 'last'. Specifies how to handle NULL values. 'first' means put them first, 'last' means put them last. |
sort_remaining | True |
Optional, default True. Specifies whether to sort by other levels as well, or not |
ignore_index | True |
Optional, default False. Specifies whether to ignore index or not. If True the original indexes are ignored, and replaced by 0, 1, 2 etc. |
key | Function | Optional, specify a function to be executed before the sorting |
Return Value
A DataFrame with the sorted result, or None if the inplace parameter is set to True.
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