How to use the Pandas library in Python

Pandas is a popular Python library for data manipulation and analysis. It is built on top of the NumPy library and provides easy-to-use data structures and data analysis tools for working with numerical, tabular, and time series data.

Here are some examples of how to use the Pandas library in Python:

• Import the Pandas library:

import pandas as pd

• Read a CSV file into a Pandas DataFrame:

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

• View the first few rows of the DataFrame:

df.head()

• Select a column from the DataFrame:

df["column_name"]

• Filter the DataFrame to only include rows with certain values in a column:

df[df["column_name"] == "value"]

• Calculate the mean of a column:

df["column_name"].mean()

• Plot the values in a column using matplotlib:

import matplotlib.pyplot as plt

plt.plot(df["column_name"])
plt.show()

These are just a few examples of how to use Pandas for data manipulation and analysis. For more information, you can refer to the Pandas documentation:

Link