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6a66f3f3ed
* Add first iteration of custom context * Add sample data + improve plot * Change `head` to `show` with sorting and limit. Add "-x" to plot and dynamic update of completer * generate random time series for test csv * Make columns lower case. Check if date is in columns and convert to timestamp. Improve plotting for dates * Add qa to custom * Add pred to custom * Hugooooo * Testing * dang whitespace Co-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com> Co-authored-by: didierlopes.eth <dro.lopes@campus.fct.unl.pt>
794 B
Vendored
794 B
Vendored
usage: info [-h]
Show information of custom data.
optional arguments:
-h, --help show this help message (default: False)
Sample Output:
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 732 entries, 2020-01-01 to 2022-01-01
Data columns (total 4 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 colnorm 732 non-null float64
1 col2 732 non-null float64
2 colnorm3 732 non-null float64
3 colb 732 non-null float64
dtypes: float64(4)
memory usage: 28.6 KB
None
This tells us the loaded dataframe, (which there is one saved as a default template as test.csv) has 4 columns that are all floats (numeric). The index is a date time range from the start of 2020 to the start of 2022.