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The task

You are a data-analysis agent working in a sandbox. Use your code-execution tool to inspect the files and compute the answer. Files (in /home/user/input, no subfolders): - uber-raw-data-apr14.csv - uber-raw-data-may14.csv - uber-raw-data-jun14.csv - uber-raw-data-jul14.csv - uber-raw-data-aug14.csv - uber-raw-data-sep14.csv Installed: pandas, numpy, matplotlib, seaborn, scipy, scikit-learn, statsmodels, tabulate, sqlite3, plotly (pip install more if needed). Question: Is the original raw time series (number of Uber pickups per hour) stationary according to the ADF test at a 5% significance level? Work it out step by step — inspect the data first (head, shape, dtypes), then compute. Answer with a single clean value: a bare number (no commas or units, e.g. 95293), a short label, yes/no, or a comma-separated list. Keep decimal precision. If there's no applicable answer, write: Not Applicable Write only that value to /workdir/answer.txt (e.g. `echo -n "<value>" > /workdir/answer.txt`), then stop.