11. The Cheatsheet

NumPy

python
import numpy as np
a = np.array([1, 2, 3])
a.shape         # (3,)
a.dtype         # int64
np.zeros((3,3)) # 3x3 Matrix of 0s
a[a > 2]        # [3] (Boolean Mask)

Pandas Setup

python
import pandas as pd
df = pd.read_csv('data.csv', parse_dates=['date'])
df.info()       # RAM usage & Types
df.describe()   # Statistics

Selection

python
df['col']             # Series
df[['a', 'b']]        # DataFrame
df.loc[row_label]     # By Label
df.iloc[row_idx]      # By Position

Cleaning

python
df.drop_duplicates()
df.fillna(method='ffill')
df['a'] = df['a'].astype('category')

Aggregation

python
df.groupby('col').mean()
df.pivot_table(index='a', columns='b', values='c')

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