Why Explore Your Data?

Before analyzing or cleaning a dataset, it's important to understand what you're working with. Pandas provides several simple methods to quickly explore and summarize your data.

Useful Data Exploration Methods

Here are a few of the most common Pandas methods for exploring a DataFrame:

• df.head() — shows the first 5 rows
• df.tail() — shows the last 5 rows
• df.shape — returns the number of rows and columns
• df.info() — displays column types and non-null counts
• df.describe() — gives summary statistics for numerical columns

Example:

import pandas as pd
df = pd.read_csv("sales.csv")
print(df.head())
print(df.shape)
print(df.describe())

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