Pandas Tutorial for Data Science

Data Science 261 views Nov 14, 2025 1 min read

Introduction

Pandas is the most important library for data manipulation and analysis. It provides two key data structures: Series and DataFrame.


import pandas as pd

s = pd.Series([10, 20, 30])
print(s)


df = pd.DataFrame({
  "Name": ["John", "Mary"],
  "Age": [28, 34]
})
print(df)


df = pd.read_csv("data.csv")
df.head()


df["Age"]
df[["Name", "Age"]]


df[df["Age"] > 30]


df.isnull().sum()
df.fillna(0)
df.dropna()


df.sort_values("Age", ascending=False)


df.groupby("Department")["Salary"].mean()


merged = pd.merge(df1, df2, on="id")

Pandas is the heart of data analysis, making data cleaning and transformation fast and efficient.

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