Time Series Processing with Pandas: Difference between revisions

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Line 12: Line 12:
The content of the CSV file should be similar to:
The content of the CSV file should be similar to:
<font size=-2>
<font size=-2>
date, value
date, value
2023-10-01, 133
2023-10-01, 133
2023-10-02, 135
2023-10-02, 135
2023-10-03, 139
2023-10-03, 139
2023-10-04, 123
2023-10-04, 123
2023-10-05, 122
2023-10-05, 122
2023-10-06, 119
2023-10-06, 119
2023-10-07, 117
2023-10-07, 117
2023-10-08, 130
2023-10-08, 130
2023-10-09, 132
2023-10-09, 132
</font>
</font>

Revision as of 19:02, 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

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