Python 使用 nan 将数据从 6 分钟重新采样到 5 分钟

这里df_6min是df

df_5min = []

# create list of 5 minute values in an hour
list_min5 = list(range(0, 60, 5))

# for each column get pandas data series of 5 min interval resampled with linear interpolation
for column in df_6min.columns:
    ds_5min = df_6min[column].resample('1Min').interpolate(method='linear').resample('5Min').asfreq()

    # for each index of 6 min interval check if there is nan
    for i in df_6min.index:
        if np.isnan(df_6min.loc[i, column]) == True:

            # if yes replace upper and lower index of 5 min by nan  
            for j in range(len(list_min5)):

                if list_min5[j-1] < i.minute < list_min5[j]:
                    ds_5min.loc[i.replace(minute=list_min5[j-1])] = np.nan
                    ds_5min.loc[i.replace(minute=list_min5[j])] = np.nan

                # if index is 0 minute or 30 minute, get j+1 index instead of j
                if list_min5[j-1] == i.minute:
                    ds_5min.loc[i.replace(minute=list_min5[j-1])] = np.nan
                    ds_5min.loc[i.replace(minute=list_min5[j+1])] = np.nan

    df_5min.append(ds_5min)  

df_5min = pd.concat(df_5min, axis=1)