Pandas Methods Index

Every Pandas method below links to real Bamboo Weekly exercises that use it — so you can practice the method on messy, real-world data, then study the worked solution. The most-used methods have their own page listing every exercise that uses them. See also practice by skill or the full archive.

Reading & writing data · Creating & reshaping · Selecting & filtering · Grouping, aggregation & windows · Cleaning & transforming · Statistics & math · Working with text (.str) · Working with dates & times (.dt) · Plotting & inspection

Reading & writing data

• read_csv — 98 exercises
• read_excel — 60 exercises
• read_html — 20 exercises
• read_json — 4 exercises
• read_parquet — 4 exercises
• to_parquet — 3 exercises
• json_normalize — 2 exercises

Creating & reshaping

• pivot_table — 75 exercises
• join — 51 exercises
• concat — 46 exercises
• unstack — 26 exercises
• explode — 20 exercises
• DataFrame — 18 exercises
• merge — 13 exercises
• Series — 7 exercises
• stack — 5 exercises
• cut — 5 exercises
• melt — 4 exercises
• crosstab — 2 exercises
• get_dummies — 1 issue: #13 Python developers

Selecting & filtering

• pd.col new in Pandas 3.0 — 31 exercises
• loc — 162 exercises
• head — 67 exercises
• nlargest — 61 exercises
• iloc — 51 exercises
• isin — 51 exercises
• filter — 34 exercises
• xs — 27 exercises
• tail — 16 exercises
• nsmallest — 16 exercises
• idxmax — 15 exercises
• select_dtypes — 9 exercises
• idxmin — 7 exercises
• query — 4 exercises
• where — 1 issue: #66 Pittsburgh
• between — 1 issue: #159 State of the Union

Grouping, aggregation & windows

• groupby — 104 exercises
• pipe — 63 exercises
• agg — 61 exercises
• pct_change — 56 exercises
• resample — 49 exercises
• apply — 39 exercises
• diff — 33 exercises
• map — 13 exercises
• rank — 6 exercises
• rolling — 3 exercises
• expanding — 2 exercises
• shift — 2 exercises
• transform — 1 issue: #157 Government corruption

Cleaning & transforming

• assign — 114 exercises
• sort_values — 109 exercises
• set_index — 108 exercises
• drop — 77 exercises
• astype — 75 exercises
• replace — 60 exercises
• dropna — 58 exercises
• reset_index — 53 exercises
• to_datetime — 47 exercises
• rename — 29 exercises
• sort_index — 27 exercises
• fillna — 16 exercises
• isna — 13 exercises
• drop_duplicates — 13 exercises
• set_axis — 13 exercises
• interpolate — 8 exercises
• ffill — 5 exercises
• notna — 5 exercises
• to_numeric — 2 exercises
• duplicated — 1 issue: #91 Roller coasters
• clip — 1 issue: #24 Wildfire smoke

Statistics & math

• mean — 87 exercises
• sum — 72 exercises
• value_counts — 71 exercises
• corr — 39 exercises
• count — 36 exercises
• max — 22 exercises
• round — 13 exercises
• describe — 11 exercises
• min — 9 exercises
• median — 7 exercises
• nunique — 5 exercises
• abs — 5 exercises
• quantile — 4 exercises
• std — 3 exercises
• unique — 2 exercises
• mode — 1 issue: #94 Strategic Wine Reserve
• last — 1 issue: #181 Housing costs

Working with text (.str)

• str.replace — 32 exercises
• str.contains — 30 exercises
• str.split — 24 exercises
• str.strip — 19 exercises
• str.get — 14 exercises
• str.len — 12 exercises
• str.lower — 10 exercises
• str.slice — 10 exercises
• str.startswith — 8 exercises
• str.removesuffix — 5 exercises
• str.title — 4 exercises
• str.removeprefix — 3 exercises
• str.extract — 1 issue: #172 World Cup
• str.upper — 1 issue: #32 Unions
• str.endswith — 1 issue: #159 State of the Union
• str.zfill — 1 issue: #101 Los Angeles Fires

Working with dates & times (.dt)

• dt.year — 41 exercises
• dt.month — 17 exercises
• dt.day_name — 6 exercises
• dt.hour — 4 exercises
• dt.date — 3 exercises
• dt.month_name — 2 exercises
• dt.dayofweek — 2 exercises
• dt.quarter — 2 exercises
• dt.total_seconds — 2 exercises
• dt.day — 1 issue: #71 Holidays
• dt.days — 1 issue: #76 Aging legislators

Plotting & inspection

• plot.hist Pandas built-in plotting — 3 exercises
• memory_usage — 11 exercises
• plot — 2 exercises
• info — 2 exercises