current position：Home>Find a pandas (dataframe) grouping problem to find rank
Find a pandas (dataframe) grouping problem to find rank
2022-01-27 03:00:24 【CSDN Q & A】
My needs ： such as
Yes 1 individual 2021 year 12 Since A Daily trading records of shares （dataframe）, There are three columns ： Stock code ：code, Market value ：mv, Transaction date ：date
, I want to use group 、rank And other methods to find a stock （ such as ：'000001'） Market value on each trading date （mv） Ranking in all stocks （rank）, I don't have any ideas .
Please ask ！
Refer to the answer 1：
import pandas as pddata = [[101, 236423, '2021-01'], [101, 223387, '2021-02'], [102, 397845, '2021-01'], [102, 138257, '2021-02'], [103, 83475, '2021-01'], [103, 393475, '2021-02']]df = pd.DataFrame(data=data, columns=['code', 'mv', 'date'])print(df)def f(series): tmpDf = pd.merge(series,df,on ='date') res = tmpDf.groupby(by='date').apply(lambda x: ((x['code_y'] !=x['code_x']) return res df = df.groupby('code').apply(f)print(df)'''--result code mv date0 101 236423 2021-011 101 223387 2021-022 102 397845 2021-013 102 138257 2021-024 103 83475 2021-015 103 393475 2021-02 date countcode 101 0 2021-01 2 1 2021-02 2102 0 2021-01 1 1 2021-02 3103 0 2021-01 3 1 2021-02 1'''
Refer to the answer 2：
author[CSDN Q & A],Please bring the original link to reprint, thank you.
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