Pandas Fundamentals in 40 Minutes

Pandas Is the Table API

Pandas was created in 2008 by Wes McKinney at a hedge fund. Today it is the default Python library for tabular data, downloaded over 100 million times per month. Its two main types are Series (a single column) and DataFrame (a table).

Ten verbs you will use constantly

import pandas as pd # 1. Load df = pd.read_csv('data.csv') # 2. Peek df.head() df.info() df.describe() # 3. Select columns df['age'] # one column (Series) df[['age', 'income']] # multiple columns (DataFrame) # 4. Filter rows df[df['age'] > 18] df[(df['age'] > 18) & (df['country'] == 'US')] # 5. Sort df.sort_values('income', ascending=False) # 6. Create columns df['income_per_age'] = df['income'] / df['age'] # 7. Group and aggregate df.groupby('country')['income'].mean() df.groupby(['country', 'gender']).agg({ 'income': ['mean', 'median'], 'age': 'mean' }) # 8. Join tables merged = pd.merge(df, other_df, on='user_id', how='left') # 9. Pivot pd.pivot_table(df, index='country', columns='year', values='income') # 10. Save df.to_csv('clean.csv', index=False) df.to_parquet('clean.parquet')The ten most important pandas operations

Indexing: the most confusing part

# .loc uses labels df.loc[5] # row with index label 5 df.loc[df['age'] > 18, 'name'] # name column, filtered rows # .iloc uses positions df.iloc[5] # 6th row regardless of index label df.iloc[:10, :3] # first 10 rows, first 3 cols # Chained assignment is a trap # df[df.age > 18]['score'] = 100 # DO NOT DO THIS df.loc[df.age > 18, 'score'] = 100 # CORRECTCorrect indexing patterns

Common patterns worth memorizing

# Top N per group top3 = df.groupby('country').apply( lambda g: g.nlargest(3, 'income') ).reset_index(drop=True) # Rolling stats df['7d_avg'] = df['sales'].rolling(window=7).mean() # Replace based on mapping df['country'] = df['country'].replace({'USA': 'US', 'U.S.A.': 'US'}) # One-hot encoding df_encoded = pd.get_dummies(df, columns=['color']) # Handle dates df['date'] = pd.to_datetime(df['date']) df['day_of_week'] = df['date'].dt.day_name()Patterns you will use every week

The big idea: pandas rewards the ten verbs you use 90 percent of the time. Master those before chasing fancier features, and the other 10 percent will come naturally when you need it.