Python Data Analysis: GroupBy, Merge, Time Series & Plots
Group, merge, reshape, clean and resample fictional business data with pandas, predict exactly what each line of code returns and plot the results, with every answer checked as you go.
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About this course
In this intermediate course you analyse fictional business data the way pandas does. Every lab shows real pandas code next to the data, and you predict exactly what it returns: groupby summaries with size, count, sum and nunique, transform and filter, ranking inside groups, inner and left merges with the duplicate-key trap, concat and drop_duplicates, pivot_table margins, melt, missing values, ffill and interpolate, the .dt accessor, weekly resampling, rolling averages, growth with pct_change and line and bar charts. A final project merges, filters, groups and ranks a margin report. Each answer is checked instantly, and a 15-question exam leads to your certificate.
Lessons
- First Look: Sum, Mean & value_counts on a Real Orders TableFree
- Boolean Masks: Filtering Rows with &, | and ~ Locked
- groupby Basics: size, sum and mean per Region Locked
- size vs count: Groups with Missing Values Locked
- Named Aggregation: min, max and nunique in One Report Locked
- Two Keys and unstack: From MultiIndex to Cross-Table Locked
- transform: Group Totals and Shares on Every Row Locked
- Filtering Whole Groups: groupby().filter() as HAVING Locked
- Ranking Inside Groups: rank, cumcount and Top-N Locked
- merge on a Key: What an Inner Join Keeps and Drops Locked
- Left Joins, indicator=True and the Duplicate-Key Trap Locked
- concat and drop_duplicates: Combining Overlapping Exports Locked
- pivot_table: Default mean, aggfunc and margins Locked
- melt: From Wide Spreadsheets to Tidy Long Data Locked
- Missing Values: isna, fillna and dropna Without Fooling Yourself Locked
- Gaps in a Series: ffill, bfill and interpolate Locked
- Dates with the .dt Accessor: Weekdays, Weekends and Names Locked
- resample: Weekly Totals, Counts and Means from Raw Orders Locked
- Rolling Windows: Moving Averages and min_periods Locked
- shift, diff and pct_change: Month-over-Month Growth Locked
- Plotting with pandas: Line for Time, Bars for Categories Locked
- Final Project: Merge, Filter, Group and Rank a Margin Report Locked