pandas read xls

You can use pandas to read data from an Excel file into a DataFrame, and then work with the data just like you would any other dataset.

To read an Excel file into a DataFrame using pandas, you can use the read_excel() function. The read_excel() function returns a DataFrame by default, so you can access the data in your DataFrame using standard indexing and slicing operations.

Pandas, a data analysis library, has native support for loading excel data (xls and xlsx). The method read_excel loads xls data into a Pandas dataframe:

read_excel(filename)

If you have a large excel file you may want to specify the sheet:

df = pd.read_excel(file, sheetname='Elected presidents')

Related course
Data Analysis with Python Pandas

Read excel with Pandas
The code below reads excel data into a Python dataset (the dataset can be saved below).

from pandas import DataFrame, read_csv
import matplotlib.pyplot as plt
import pandas as pd 

file = r'data/Presidents.xls'
df = pd.read_excel(file)
print(df['Occupation'])

The dataframe can be used, as shown in the example below:

from pandas import DataFrame, read_csv
import matplotlib.pyplot as plt
import pandas as pd 

file = r'data/Presidents.xls'
df = pd.read_excel(file)

# remove messy data
df = df[df['Years in office'] != 'n/a']

# show data
print('Min: ', df['Years in office'].min())
print('Max: ', df['Years in office'].max())
print('Sum: ', df['Years in office'].sum())

Dataset
For purpose of demonstration, you can use the dataset from: depaul.edu.

A large dataset stored in XLS format

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