Here are four approaches to reading text files in Pandas. One thing I want to share with you is there is no direct method for reading text. However, you can achieve it using the read_csv and fwf methods.
Table of contents
Approaches to Read Text Files in Pandas
- When you work with Pandas, reading text files is a common task and there are different methods to accomplish this.
- In Pandas, you can use
read_csv,read_table,read_fwf,read_excel, andread_htmlto read different types of text files such as delimited data, fixed-width formatted files, Excel spreadsheets, or HTML tables. - Each method serves a specific purpose and can be used for specific types of text files. Pandas provides a variety of tools to efficiently handle diverse text file formats. Let’s explore these methods and understand how to read text files using Pandas.
read_csv()
This method is commonly used to read text files with delimited data, such as CSV files. For example:
mport pandas as pd
df = pd.read_csv('file.txt', delimiter='\t')read_table()
This method is similar to read_csv() but assumes the delimiter is a tab character (‘\t’) by default. For example:
import pandas as pd
df = pd.read_table('file.txt')read_fwf()
This method reads fixed-width formatted files, where the data is arranged in columns of specified widths. For example:
import pandas as pd
df = pd.read_fwf('file.txt', widths=[10, 8, 12])read_excel()
This method can read text files saved in Excel format (.xls or .xlsx). For example:
import pandas as pd
df = pd.read_excel('file.xlsx', sheet_name='Sheet1')read_html()
This method is used to read tables from HTML files or web pages. It returns a list of dataframes, one for each table found in the HTML. For example:
import pandas as pd
dfs = pd.read_html('file.html')
df = dfs[0] # Assuming the first table is of interestThese are some of the commonly used methods, but there are other specialized methods available in Pandas for specific file formats.
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