Time Series Processing with Pandas: Difference between revisions
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The content of the CSV file should be similar to: | The content of the CSV file should be similar to: | ||
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</ | date, value | ||
2023-10-01, 133 | |||
2023-10-02, 135 | |||
2023-10-03, 139 | |||
2023-10-04, 123 | |||
2023-10-05, 122 | |||
2023-10-06, 119 | |||
2023-10-07, 117 | |||
2023-10-08, 130 | |||
2023-10-09, 132 | |||
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Revision as of 19:01, 8 October 2023
Internal
Overview
This article provides hints on how time series can be processed with Pandas.
Load a Time Series
Assuming the data comes from a CSV file whose first column, labeled "date", contains timestamp-formatted strings, and the second column contains values corresponding to those timestamps, this is how the data is loaded and turned into a Pandas Series.
The content of the CSV file should be similar to: date, value 2023-10-01, 133 2023-10-02, 135 2023-10-03, 139 2023-10-04, 123 2023-10-05, 122 2023-10-06, 119 2023-10-07, 117 2023-10-08, 130 2023-10-09, 132