The only pandas course built around real data problems. From loading your first CSV to processing datasets too large to fit in memory — every lesson ships working code you can use on your own data.
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import pandas as pd df = pd.read_csv("sales_2024.csv") df = df.dropna().drop_duplicates() monthly = df.groupby("month")["revenue"].agg( total="sum", avg="mean", count="count" ).reset_index() print(monthly.sort_values("total", ascending=False))
Most pandas tutorials teach you methods in isolation. This course teaches you to think in DataFrames — the same way data scientists who get paid to use pandas actually think.
Every lesson uses real-world-style data: sales reports, time series, messy CSVs with nulls and wrong dtypes. Not toy examples with three rows.
Day 5 covers vectorization, chunking, and handling datasets larger than RAM. Skills that separate junior from senior data practitioners.
Every code block runs. No "exercise left to the reader." You finish each day with something working on your machine.
Read CSVs, Excel files, and JSON. Inspect shape, dtypes, and nulls. Select rows and columns with loc, iloc, and boolean filtering.
Handle nulls with fillna and dropna. Remove duplicates. Fix wrong data types. Build a reusable cleaning pipeline.
Aggregate with groupby. Reshape with pivot_table. Combine DataFrames with merge and concat. Apply custom functions row-by-row.
Parse dates, resample by period, rolling averages, shifting, and DatetimeIndex. Everything you need for financial or operational time series.
Stop using apply() for everything. Use vectorized operations for 100x speedups. Process files larger than RAM with chunking. Profile and fix slow code.
Drop your email and we'll send you Day 1 plus a cheat sheet of the 20 pandas methods you'll use 80% of the time.
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3 days of hands-on training with a practitioner instructor. Small groups, real projects, and a network of peers building the same skills.
You need basic Python — variables, loops, functions. If you don't have that yet, take our free Python for AI course first, then come back.
Yes. All 5 days, forever. We make money from bootcamp seats, not course paywalls.
pandas 2.x. The code works on 1.x too with minor differences — we note them where they matter.
60–75 minutes per day. Self-paced, so take as long as you need. Most people finish in 5–7 days total.