I split a dataframe from minute to daily, weekly and monthly. I had no problem to reformat the daily dataframe, though I am having a good bit of trouble trying to do the same with the weekly one. Here is the weekly dataframe if someone could help me out please, it would be great.
I am adding the code I used to reformat the daily dataframe, so it may helps!
I am plotting it with Bokeh and without the datetime format I won't be able to format the axis and hovertools as I would like.
Thanks beforehand.
dfDay1 = dfDay.loc['2014-01-01':'2020-09-31']
dfDay1 = dfDay1.reset_index()
dfDay1['date1'] = pd.to_datetime(dfDay1['date'], format=('%Y/%m/%d'))
dfDay1 = dfDay1.set_index('date')
That worked fine for the day format.
If need convert dates before / use Series.str.split with str[0], if dates after / use str[1]:
df['date1'] = pd.to_datetime(df['week'].str.split('/').str[0])
print (df)
week Open Low High Close Volume \
0 2014-01-07/2014-01-13 58.1500 55.38 58.96 56.0000 324133239
1 2014-01-14/2014-01-20 56.3500 55.96 58.57 56.2500 141255151
2 2014-01-21/2014-01-27 57.8786 51.85 59.31 52.8600 279370121
3 2014-01-28/2014-02-03 53.7700 52.75 63.95 62.4900 447186604
4 2014-02-04/2014-02-10 62.8900 60.45 64.90 63.9100 238316161
.. ... ... ... ... ... ...
347 2020-09-01/2020-09-07 297.4000 271.14 303.90 281.5962 98978386
348 2020-09-08/2020-09-14 275.0000 262.64 281.40 271.0100 109717114
349 2020-09-15/2020-09-21 272.6300 244.13 274.52 248.5800 123816172
350 2020-09-22/2020-09-28 254.3900 245.40 259.98 255.8800 98550687
351 2020-09-29/2020-10-05 258.2530 256.50 268.33 261.3500 81921670
date1
0 2014-01-07
1 2014-01-14
2 2014-01-21
3 2014-01-28
4 2014-02-04
.. ...
347 2020-09-01
348 2020-09-08
349 2020-09-15
350 2020-09-22
351 2020-09-29
[352 rows x 7 columns]