Nav*_*ala 6 python dataframe pandas
我有一个像这样的熊猫数据框:
column_year column_Month a_integer_column
0 2014 April 25.326531
1 2014 August 25.544554
2 2015 December 25.678261
3 2014 February 24.801187
4 2014 July 24.990338
... ... ... ...
68 2018 November 26.024931
69 2017 October 25.677333
70 2019 September 24.432361
71 2020 February 25.383648
72 2020 January 25.504831
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我现在想先对年份列进行排序,然后对月份列进行排序,如下所示:
column_year column_Month a_integer_column
3 2014 February 24.801187
0 2014 April 25.326531
4 2014 July 24.990338
1 2014 August 25.544554
2 2015 December 25.678261
... ... ... ...
69 2017 October 25.677333
68 2018 November 26.024931
70 2019 September 24.432361
72 2020 January 25.504831
71 2020 February 25.383648
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我该怎么做呢?
让我们试试to_datetime+ argsort:
df=df.iloc[pd.to_datetime(df.column_year.astype(str)+df.column_Month,format='%Y%B').argsort()]
column_year column_Month a_integer_column
3 2014 February 24.801187
0 2014 April 25.326531
4 2014 July 24.990338
1 2014 August 25.544554
2 2015 December 25.678261
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您可以将column_Month列更改为CategoricalDtype
Months = pd.CategoricalDtype([
'January', 'February', 'March', 'April', 'May', 'June',
'July', 'August', 'September', 'October', 'November', 'December'
], ordered=True)
df.astype({'column_Month': Months}).sort_values(['column_year', 'column_Month'])
column_year column_Month a_integer_column
3 2014 February 24.801187
0 2014 April 25.326531
4 2014 July 24.990338
1 2014 August 25.544554
2 2015 December 25.678261
69 2017 October 25.677333
68 2018 November 26.024931
70 2019 September 24.432361
72 2020 January 25.504831
71 2020 February 25.383648
Run Code Online (Sandbox Code Playgroud)