Pandas read_table() Function Syntax

Below is the syntax of pandas.read_table() function.

Syntax: pandas.read_table(filepath_or_buffer, delimiter=None, header=’infer’, names=None, index_col=None, usecols=None, dtype=None, skiprows=None, na_values=None, parse_dates=False, encoding=None, comment=None)

Parameters:

• filepath_or_buffer: The path or object representing a file to be read.
• delimiter: The delimiter to use, in this case, it’s retained for specifying the column separator.
• header: Row(s) to use as the column names.
• names: List of column names to use.
• index_col: Column(s) to set as index (can be a single column name or a list of names).
• usecols: Columns to read from the file.
• dtype: Data type to force.
• skiprows: Number of rows to skip at the beginning of the file.
• na_values: Additional strings to recognize as NA/NaN.

Returns: A comma(‘,’) separated values file(csv) is returned as two dimensional data with labelled axes.

To get the link to csv file used in the article, click here.

Pandas is one of the most used packages for analyzing data, data exploration, and manipulation. While analyzing real-world data, we often use the URLs to perform different operations and Pandas provide multiple methods to read tabular data in Pandas. One of those methods is read_table()