Read Different File Formats

Read the following file formats using Pandas.

1. Text Files
2. CSV Files
3. Excel Files
4. JSON Files

Read text files.

In the current working directory, first create a text file with the following text and saved with the name CarsInfo.txt.

Program

fo = open("CarsInfo.txt","r")
carsInfo = fo.read()
fo.close()
print("Cars Information:")
print(carsInfo)

Output

Cars Information:
name    showroomprice   onroadprice
tata            6.32            8.02
benz            12.50           16.80
bmw             24.60           29.60
tata            10.60           14.80

Read CSV Files

In the current working directory, first create a CSV file with the following details and saved with the name CarsInfo.csv.

Program

import pandas as pd

csv = pd.read_csv("CarsInfo.csv")
print("Cars Information:")
print(csv)

Output

Cars Information:
   Name  Show Room Price  On-Road Price
0  tata             6.32           8.02
1  benz            12.50          16.80
2   bmw            24.60          29.60
3  tata            10.60          14.80

Read Excel Files

In the current working directory, first create a excel file with the following details and saved with the name CarsInfo.xlsx and also sheet name as CarPrices.

Program

import pandas as pd

with pd.ExcelFile("CarsInfo.xlsx") as excel:
    carsInfo = pd.read_excel(excel,"CarPrices")
print("Cars Information:")
print(carsInfo)

Output

Cars Information:
   Name  Show Room Price  On-Road Price
0  tata             6.32           8.02
1  benz            12.50          16.80
2   bmw            24.60          29.60
3  tata            10.60          14.80

Read JSON Files

In the current working directory, first create a JSON file as follows shown below and saved with the name CarsInfo.json.

Program

import json

with open("CarsInfo.json") as fo:
    jsonData = json.load(fo)
print("Cars Information:")
print(jsonData)

Output

Cars Information:
{'name': ['benz', 'bmw', 'tata'], 'showroomprice': [12.5, 24.6, 10.6], 'onroadprice': [16.8, 29.6, 14.8]}