174.24 MB | 00:05:39 | mp4 | 1280X720 | 16:9
01 – Effectively present data with Python.mp4 (3.36 MB)
03 – Using the exercise files.mp4 (1014.76 KB)
01 – Value of data visualization.mp4 (1.35 MB)
02 – Leverage programming languages.mp4 (4.31 MB)
03 – Overview of Jupyter Notebooks.mp4 (2.71 MB)
01 – Introduction to pandas.mp4 (2.63 MB)
02 – Create sample data.mp4 (10.98 MB)
03 – Load sample data.mp4 (6.03 MB)
04 – Basic operations.mp4 (4.49 MB)
05 – Simplify with slicing.mp4 (9.22 MB)
06 – Filter and clean data.mp4 (12.1 MB)
07 – Rename and delete columns.mp4 (7.15 MB)
08 – Aggregate functions.mp4 (6.6 MB)
09 – Identify missing data.mp4 (8.39 MB)
10 – Remove or fill in missing data.mp4 (11.32 MB)
11 – Convert pandas DataFrames.mp4 (3.35 MB)
12 – Export pandas DataFrames.mp4 (3.3 MB)
01 – Basics of Matplotlib.mp4 (9.49 MB)
02 – Set marker type and colors.mp4 (4.05 MB)
03 – MATLAB-style vs object syntax.mp4 (4.09 MB)
04 – Set titles, labels, and limits.mp4 (10.22 MB)
05 – Add grids.mp4 (5.28 MB)
06 – Create legends.mp4 (3.65 MB)
07 – Save plots to files.mp4 (6.19 MB)
08 – Create plots with Matplotlib wrappers.mp4 (11.13 MB)
01 – Create heatmaps.mp4 (8.59 MB)
02 – Create histograms.mp4 (7.36 MB)
03 – Create subplots.mp4 (10.66 MB)
01 – Next steps.mp4 (3.09 MB)
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