Step 1: Set Up Environment and Master Data Basics
Start with Google Colab for a free, no-install setup.
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Open Google Colab and create a new notebook.
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Install essential libraries:
!pip install pandas numpy scikit-learn matplotlib seaborn
- Load and explore a sample dataset (Iris from scikit-learn):
import pandas as pd
from sklearn.datasets import load_iris
import matplotlib.pyplot as plt
iris = load_iris()
df = pd.DataFrame(iris.data, columns=iris.feature_names)
df['target'] = iris.target
print(df.head())
print(df.describe())
df['sepal length (cm)'].hist()
plt.show()
Practice filtering and grouping:
print(df.groupby('target').mean())
