Pandas is an open source library which is built on top of NumPy library. It allows user for fast analysis, data cleaning & preparation of data efficiently. Pandas is fast and it has high-performance & productivity for users.
Most of the datasets you work with are called DataFrames. DataFrames is a 2-Dimensional labeled Data Structure with index for rows and columns, where each cell is used to store a value of any type. Basically, DataFrames are Dictionary based out of NumPy Arrays.
Let’s see how to save a Pandas DataFrame as a CSV file using
Example #1: Save csv to working directory.
Example #2: Saving CSV without headers and index.
Example #3: Save csv file to a specified location.
Example #4: Write a DataFrame to CSV file using tab separator.
Original DataFrame: Name Age 0 Amit 20 1 Cody 21 2 Drew 25 Data from Users.csv: Name\tAge 0 Amit\t20 1 Cody\t21 2 Drew\t25
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