Stack Overflow Asked by Spatial Digger on February 23, 2021
I have some data
that look like this:
{'open_time': [0 2021-02-14 19:30:00
1 2021-02-14 19:31:00
2 2021-02-14 19:32:00
3 2021-02-14 19:33:00
4 2021-02-14 19:34:00
...
494 2021-02-15 03:44:00
495 2021-02-15 03:45:00
496 2021-02-15 03:46:00
497 2021-02-15 03:47:00
498 2021-02-15 03:48:00
Name: 0, Length: 499, dtype: datetime64[ns]], 'open': [0 4.195
1 4.192
2 4.192
3 4.195
4 4.196
I try to turn it into a dataframe:
h_kline = pd.DataFrame(data)
but all the data end up as a sinfgle row in the column like: 0 2021-02-14 19:31:00n1 2021-02-14 19:32:00n2
etc.
Where have I gone wrong?
The dictionary was constructed like this:
data = {'open_time': [open_time], 'open': [open], 'high': [high], 'low': [low], 'close': [close], 'close_time': [close_time], 'volumne': [volume]}
the values in [ ]
are pandas series
If you give the DataFrame method a dictionary, the keys will be the columns and the values the rows. If you want to specify the order of the columns in your new data frame, you can also specify a columns parameter and set it to the list of column header labels.
Answered by not_overrated on February 23, 2021
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