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Nowadays, the use of Pandas DataFrames is most popular in Data Science. Using Pandas library, we can load and read data from different types of files like csv, tsv, xlsetc.

Most of the users tsvstore their data in file format. So, in this case, we should know how to load tsva file and read data from that file format.

TSV stands for Tab Separated Values. It is a simple text file format used to store data in a tabular structure.

For example, we can tsvstore spreadsheets or database tables in CSV format to exchange information between different databases.

The TSV file format is similar to the CSV file format, but in .tsvthe file, the data is tab-delimited in plain text.

tsvWe will demonstrate how to load a file into Pandas in this tutorial DataFrame. We will provide different examples to dataframesread tsvfile data using Pandas.

Basic syntax for reading TSV files using Pandas

This syntax pd.read_csv(file_path, sep='\t' )is used to tsvread the file into pandas DataFrame.

DataFrameLoading file data using Pandas tsvis a very simple process. First, we will import all the required modules and then load tsvthe file using the syntax mentioned above.

Loading TSV files using Pandas DataFrame

DataFrameTo load a file using pandas tsv, use read_csv()the method.

\tLoad tsvthe file into pandas using the delimiter DataFrame.

In the following example, we have loaded a file using pandas by using read_csv(file_path, sep='\t')the file path and format specifier in the method as arguments .\tDataFrametsv

import pandas as pd

# testdata.tsv is stored in PC
dataframe = pd.read_csv("C:\\Users\\DELL\\OneDrive\\Desktop\\testdata.tsv", sep="\t")
dataframe

Output:

If we do not expand the file path by the separator \t, we will receive the following output on the terminal.

import pandas as pd

# testdata.tsv is stored in PC
dataframe = pd.read_csv("C:\\Users\\DELL\\OneDrive\\Desktop\\testdata.tsv")
dataframe

Output:

Use the header parameter to tsvload the file into pandasDataFrame

We can read.csv()pass the header as a parameter in the method. If the dataset header is present, use header=0as parameter.

import pandas as pd

# testdata.tsv is stored in PC
dataframe = pd.read_csv(
    "C:\\Users\\DELL\\OneDrive\\Desktop\\testdata.tsv", sep="\t", header=0
)
dataframe

Output:

Similarly, we can also display multiple rows as headers. For example, we want to display the first three rows as header=[1,2,3].

To implement this approach, see the example given below:

import pandas as pd

# testdata.tsv is stored in PC
dataframe = pd.read_csv(
    "C:\\Users\\DELL\\OneDrive\\Desktop\\testdata.tsv", sep="\t", header=[1, 2, 3]
)
dataframe

Output:

in conclusion

This tutorial shows how to tsvload .txt files into Pandas DataFrame. Above, we demonstrated tsvdifferent examples of loading .txt files.

Test all the above examples on your python notebook for better understanding.