Python pandas 为周和年以及月和年创建日期时间

Question

I'm have a pandas dataframe with: Branch, Year, Month, Week, Assignments, Sales Volume

picture:

I'm trying to display multiple years on my plotly dashboard based and Month.Year and Week.Year

like on this picture I'm dispaying two years with Year Month on the Xaxis:

on this picture you can see that this years are ordered in a timeline from 2018-2019.

My problem im trying to create datetime based and week.year = (52.2018) and month.year = (12.2019) but I cant create datetimes like week.year or month.year im getting from this code:

dff['monthYear'] = pd.to_datetime(dff.Monat.astype(str) + '-' + dff.Jahr.astype(str), format='%m-%y')

This error:

File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\tools\datetimes.py", line 456, in _convert_listlike_datetimes values, tz = conversion.datetime_to_datetime64(arg)

File "pandas_libs\tslibs\conversion.pyx", line 350, in pandas._libs.tslibs.conversion.datetime_to_datetime64

TypeError: Unrecognized value type: <class 'str'>

During handling of the above exception, another exception occurred:

Traceback (most recent call last):

File "C:\Users\User\Desktop\DashProjekt\Jonen\ProjektBA\MultiYeartest.py", line 24, in dff['monthYear'] = pd.to_datetime(dff.Monat.astype(str) + '-' + dff.Jahr.astype(str), format='%m-%y')

File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\tools\datetimes.py", line 801, in to_datetime cache_array = _maybe_cache(arg, format, cache, convert_listlike)

File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\tools\datetimes.py", line 178, in _maybe_cache cache_dates = convert_listlike(unique_dates, format)

File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\tools\datetimes.py", line 460, in _convert_listlike_datetimes raise e

File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\tools\datetimes.py", line 423, in _convert_listlike_datetimes result, timezones = array_strptime(

File "pandas_libs\tslibs\strptime.pyx", line 150, in pandas._libs.tslibs.strptime.array_strptime

ValueError: unconverted data remains: 20

Thank you in advance.

Greeting LittleStudent

Answer 1

1. concatenate as strings with '-'
2. convert to datetime
3. reformat the datetime in plotly

df.head()
###
   Year  Month  Sales Volume
0  2020      1    773.956049
1  2020      2    438.878440
2  2020      3    858.597920
3  2020      4    697.368029
4  2020      5     94.177348


df['ym'] = df['Year'].astype(str) + '-' + df['Month'].astype(str)
df['ym'] = pd.to_datetime(df['ym'], format='%Y-%m')

fig = px.bar(df, x='ym', y='Sales Volume', color=df['Year'].astype(str))
fig.update_xaxes(tickformat='%Y_%m', tickangle=45)
fig.show()