# Entry
You can download all scripts on GitHub.
# 1. Resampling and aggregating irregular time series
// Pain point
// What the script does
Takes a CSV or Excel file with a datetime column and one or more columns of values, resamples at the specified frequency, and applies aggregate functions to each column. Fills in or highlights gaps and writes a pristine output file with a summary of what was changed.
// How it works
The script parses the datetime column with pandassets it as index and uses it resample() with configurable frequency sequences. Column aggregation methods are defined in the configuration, so the temperature column can apply the average and the sales column can apply the total. Missing intervals after resampling are handled by forward padding, interpolation, or explicit NaN flagging, depending on the settings. The gap report lists all intervals where data was missing in the original.
# 2. Detecting anomalies in time series data
// Pain point
// What the script does
// How it works
⏩ Download the anomaly detector script
# 3. Decomposition of the series into trend, seasonality and residuals
// Pain point
// What the script does
// How it works
# 4. Forecasting using a seasonal integrated autoregressive moving average
// Pain point
// What the script does
// How it works
⏩ Download the SARIMA forecast script
# 5. Comparing multiple time series
// Pain point
// What the script does
// How it works
# Summary
To get started, first download the script you plan to apply and install all the dependencies listed in its README file. Then update the configuration section at the top of the script to match the specified data and column names. Before running it on the full dataset, test the script on a tiny sample to confirm that the output is correct. Once you’re satisfied with the results, you can schedule them or integrate them into your existing data pipeline.
Have fun analyzing!
Priya C’s girlfriend is a software developer and technical writer from India. He likes working at the intersection of mathematics, programming, data analytics and content creation. Her areas of interest and specialization include DevOps, data analytics and natural language processing. She likes reading, writing, coding and coffee! He is currently working on learning and sharing his knowledge with the developer community by writing tutorials, guides, reviews, and more. Bala also creates engaging resource overviews and coding tutorials.