What is the difference between save a pandas dataframe to pickle and to csv?

Learn, what is the difference between save a pandas dataframe to pickle and to csv?
Submitted by Pranit Sharma, on November 29, 2022

Pandas is a special tool that allows us to perform complex manipulations of data effectively and efficiently. Inside pandas, we mostly deal with a dataset in the form of DataFrame. DataFrames are 2-dimensional data structures in pandas. DataFrames consist of rows, columns, and data.

Difference between save a pandas dataframe to pickle and to csv

The confusion between these two arises because Pickle is used to save the dataframe to the disk, however, to_csv() saves the CSV file in the folder which also means it saves the file in the disk. So, we need to understand why we want to save a data frame using Pickle rather than save it to CSV.

The reason why we use CSV format to save the file is that CSV files are human-readable and also, they are cross-platform which means they can be used on any platform.

But CSV file also has their demerits, for example, CSV files are slower to parse and read they require more disc space and also, and they do not preserve types in some cases which mean that sometimes while creating a CSV file some data types get mixed with the others, for example, integer to float.

If we talk about the pickle format, they are fast saving and fast loading formats, and also, they require less disk space but the benefits of CSV files are the demerits of pickle formats which means they are non-human readable and they can be generated via Python programming language only.

One can easily understand a vehicle in such a way that vehicle is a serial is two ways of storing a Pandas dataframe. By using a pickle, one is writing down the exact representation of the data frame to disk, this means that the types of columns and the indices are the same.

On the other hand, if we simply save a file as CSV we are just storing it as a separate list, and depending on the type of data set, some information will be lost when we load or backup.

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