Author(s): Gencay I.

Originally published on Towards AI.

Automate Data Analysis with Pandas

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Pandas is undoubtedly the most powerful data science library, but what if I told you that you could automate data analysis and complete your work with just a click?

In this article, we’ll explore how to do this, but first, let’s look at what the final script will look like.

Now, we would have 8 steps to achieve this;

SS of the output

Here, you can upload any CSV files you want and see;

First rowsLast rowsData typesStatistical SummaryMissing ValuesCorrelation Matrix

After just one click. Also, you can see ;

Value CountsUnique ValuesHistogramBox plot

of the columns you have selected.

Before doing that, let’s set up the environment.

pip install pandas numpy ipywidgets matplotlib seaborn

Now, let’s create a place where you can upload the dataset at the end and import the libraries.

import pandas as pdimport numpy as npimport ipywidgets as widgetsfrom ipywidgets import FileUploadfrom IPython.display import display, clear_outputimport matplotlib.pyplot as pltimport seaborn as snsimport io# Output area for displaying resultsoutput = widgets.Output()# File upload widget to upload CSV filesupload_widget = FileUpload( accept='.csv', multiple=False, description='Upload CSV File')# Display the widgetdisplay(upload_widget)

At this step, we will define the… Read the full blog for free on Medium.

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Published via Towards AI