sort the order of dataframes in a list of dataframes based on a value in each dataframe-CodePudding

I have a list of dataframe and I want to sort the order they are in the list

Each dataframe has the same structure as shown below

df1 = pd.DataFrame.from_dict({'Ch1': {0: -28, 1: -36, 2: -39, 3: -16}, 'Ch2': {0: 543, 1: 547, 2: 559, 3: 561}, 'Ch3': {0: -126, 1: -131, 2: -147, 3: -149}, 'time': {0: '2022-02-10 16.37.25.502', 1: '2022-02-10 16.37.25.502', 2: '2022-02-10 16.37.25.502', 3: '2022-02-10 16.37.25.502'}})
df2 = pd.DataFrame.from_dict({'Ch1': {0: 81, 1: 70, 2: 70, 3: 75}, 'Ch2': {0: 570, 1: 559, 2: 554, 3: 565}, 'Ch3': {0: -103, 1: -120, 2: -131, 3: -122}, 'time': {0: '2022-02-11 05.29.28.116', 1: '2022-02-11 05.29.28.116', 2: '2022-02-11 05.29.28.116', 3: '2022-02-11 05.29.28.116'}})
df3 = pd.DataFrame.from_dict({'Ch1': {0: -887, 1: -887, 2: -890, 3: -898}, 'Ch2': {0: 1307, 1: 1292, 2: 1301, 3: 1307}, 'Ch3': {0: 59, 1: 61, 2: 57, 3: 55}, 'time': {0: '2022-02-08 01.12.54.578', 1: '2022-02-08 01.12.54.578', 2: '2022-02-08 01.12.54.578', 3: '2022-02-08 01.12.54.578'}})

df_list = [df1,df2,df3]

the values in the "time" column does not change in each row within the same dataframe.

I want the dataframes in the list sorted by time (first to last) so that further processing and can match up with other data.

my attempt thus far.


for i in df_list:
    b = pd.to_datetime(i['time'].iloc[0]) #grab the first cell that contains the time stamp
    b = b.sort_values(by('time'))

returns the following error ValueError: ('Unknown string format:', '2022-02-05 08.03.09.794')

I would expect the dataframes to appear in the list with df3 being fist, df1, second and df2 last. I the time column is going and needs to be dropped for other operations therefore I would like them sorted in time order already

Any help suggestion alternative approaches greatly appreciated

CodePudding user response：

If you want to sort the rows of each dataframe, you need to provide the exact format of your datetime, and you should sort in place:

for d in df_list:
    d['time'] = pd.to_datetime(d['time'], format='%Y-%m-%d %H.%M.%S.%f')
    d.sort_values(by='time', inplace=True)

Or, if you want to sort the dataframes in the list, which is completely different, use:

df_list.sort(key=lambda d: d['time'].iloc[0])

You should be able to sort using the string due to your particular format (assuming YYYY-MM-DD).

To ensure sorting on datetime (for example if the format was MM-DD-YYYY):

df_list.sort(key=lambda d: pd.to_datetime(d['time'].iloc[0], format='%Y-%m-%d %H.%M.%S.%f'))