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Introduction to Pandas for Recommender Systems

Pandas DataFrame creation

The fundamental Pandas object is called a DataFrame. It is a 2-dimensional size-mutable, potentially heterogeneous, tabular data structure.

A DataFrame can be created multiple ways. It can be created by passing in a dictionary or a list of lists to the pd.DataFrame() method, or by reading data from a CSV file.

# Ways of creating a Pandas DataFrame
# Passing in a dictionary:
data = {'name':['Anthony', 'Maria'], 'age':[30, 28]}
df = pd.DataFrame(data)
# Passing in a list of lists:
data = [['Tom', 20], ['Jack', 30], ['Meera', 25]]
df = pd.DataFrame(data, columns = ['Name', 'Age'])
# Reading data from a csv file:
df = pd.read_csv('students.csv')

Pandas

Pandas is an open source library that is used to analyze data in Python. It takes in data, like a CSV or SQL database, and creates an object with rows and columns called a data frame. Pandas is typically imported with the alias pd.

import pandas as pd

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