Python：重新采样数据框并求和

Question

我有以下数据框：

df=pd.DataFrame(index=[0,1])
df['timestamp'] = ['2022-01-01 20:10:00', '2022-01-01 20:50:00']
df['currency'] = ['USD', 'USD']
df['operation'] = ['deposit', 'deposit']
df['amount'] = [0.1, 0.4]
df:
            timestamp           currency    operation   amount
       0    2022-01-01 20:10:00 USD         deposit     0.1
       1    2022-01-01 20:50:00 USD         deposit     0.4

如何按小时对数据重新采样并对“数量”求和以获得以下数据帧：

df:
         timestamp            currency  operation   amount
    0    2022-01-01 20:00:00  USD       deposit     0.5

使用.resample('H') 消除货币和操作列。我该怎么做才能对“金额”列求和？

Answer 1

先处理 pd.Grouper 然后再处理 agg

out = df.groupby(pd.Grouper(key='timestamp',freq='1h')).\
          agg(lambda x : x.sum() 
                         if x.dtypes == float 
                         else x.iloc[0]).reset_index()
Out[122]: 
            timestamp currency operation  amount
0 2022-01-01 20:00:00      USD   deposit     0.5

Python：重新采样数据框并求和

Python: resample dataframe and sum

python

pandas

dataframe

datetime

pandas-resample