How to read with Pandas

Operating system for this tutorial: Windows 10 system, Dell G3 computer.

Pandas is a popular Python data processing library that can be used to read and process various data formats. The following are the general steps for reading files using Pandas:

1. Import the Pandas library:

import pandas as pd

2. Use the pd.read_csv() function to read CSV file:

data = pd.read_csv('file.csv')

Where, file.csv is the path of the CSV file to be read.

3. If you want to read an Excel file, you can use the pd.read_excel() function:

data = pd.read_excel('file.xlsx')

where file.xlsx is the path to the Excel file to be read. .

4. If you want to read the data in the SQL database, you can use the pd.read_sql() function:

import sqlite3
conn = sqlite3.connect('database.db')
data = pd.read_sql('SELECT * FROM table_name', conn)

where database.db is the database file path, table_name is the name of the table to be read.

5. If you want to read a JSON file, you can use the pd.read_json() function:

data = pd.read_json('file.json')

where file.json is the path to the JSON file to be read. .

6. If you want to read a text file, you can use the pd.read_table() function:

data = pd.read_table('file.txt', delimiter=',')

where file.txt is the path of the text file to be read. , delimiter is the delimiter, here we take comma separation as an example.

The above are the general steps for reading different types of files using Pandas. Choose the appropriate function according to the actual situation, and set the corresponding parameters as needed.

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