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This tutorial explains various methods to read data in Python. Data can be in any of the popular formats - CSV, TXT, XLS/XLSX (Excel)

Loading data in python environment is the most initial step of analyzing data.

Install and Load pandas Package

pandas is a powerful data analysis package. It makes data exploration and manipulation easy. It has several functions to read data from various sources.

If you are using Anaconda, pandas must be already installed. You need to load the package by using the following command

import pandas as pd

If pandas package is not installed, you can install it by running the following code in Ipython Console. If you are using Spyder, you can submit the following code in Ipython console within Spyder.

!pip install pandas

If you are using Anaconda, you can try the following line of code to install pandas

!conda install pandas

1. Import CSV files

It is important to note that a singlebackslash does not work when specifying the file path. You need to either change it to forward slash or add one more backslash like below

import pandas as pd

import pandas as pd
mydata= pd.read_csv("C:\\Users\\Deepanshu\\Documents\\Salary_Data.csv")

2. Import File from URL

You don't need to perform additional steps to fetch data from URL. Simply put URL in read_csv() function (applicable only for CSV files stored in URL).

mydata = pd.read_csv("")

3. Read Text File

We can use read_table() function to pull data from text file. We can also use read_csv() with sep= "\t" to read data from tab-separated file.

mydata = pd.read_table("C:\\Users\\Deepanshu\\Desktop\\example2.txt")
mydata = pd.read_csv("C:\\Users\\Deepanshu\\Desktop\\example2.txt", sep ="\t")

4. Read Excel File

The read_excel() function can be used to import excel data into Python.

mydata = pd.read_excel("",sheetname="Data 1", skiprows=2)


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