Data Wrangling Assignments with pandas



Data Wrangling Assignments with pandas
Data Wrangling Assignments with pandas





Anastasia Migunova is a data scientist with wide experience in  big consulting firms among others. Currently based in Germany, she holds a Ph.D. in Applied  Maths and M.A. in Computer  Science.

The aim of this project is to replicate the tasks every data analyst or data scientist must perform to clean and analyze a dataset. The project is broken down into multiple exercises to make you practice the most used Pandas functions and tools. The project also  includes a visualization  and data analysis part  as well as some python coding.
Once you finish it, you will acquire the basic knowledge about python and its data libraries required to work with data in the real world.

You will receive an email with a protected  ZIP  and a password to access the content. If you are a  registered user, the download is always available on your account.
The downloadable zip  is made up of:
1) One PDF with the instructions and guidelines, including the project broken down into assignments so that you can finish the challenge step by step.
2) A link to the datasets you will use in the project. The datasets are public data.
3) A  Notebook file with the project solved. It contains not only the source code but also detailed explanations and comments about how the code works.
IMPORTANT: to see the solutions (Notebook) you need to have jupyter or ANACONDA package installed on your machine. If you do not have it,  you may download it here. It is free.

– Libraries: you will have to work (and install) with the following python libraries: pandas, numpy, datetime, matplotlib and  seaborn. The project includes more than 40 assignments related to:
– Import/export  gzip, csv and Excels.
Remove, select, rename, filter columns and rows.
– Nulls
– Data types.
– Groupby
– Filters
– Outliers and duplicates.
– Convert long to wide format.
– Basic Regex.
– Date formats.
– Data engineering.
– Numpy
– One hot encoding.
– Merge and joins.
– Loops (for).
– Visualization: boxplot, bars, countplot, scatterplot, heatmaps, pairwise, etc.

Python 3.7
Pandas: 0.24.2
Numpy: 1.16.4


If you need additional information, do not hesitate to contact us.


Additional information

Specification: Data Wrangling Assignments with pandas


Time Estimate

1 Day


PDF, Other

Reviews (2)

2 reviews for Data Wrangling Assignments with pandas

4.5 out of 5
Write a review
Show all Most Helpful Highest Rating Lowest Rating
  1. nick_boy (verified owner)

    Good documentation and easy to follow.
    More than 40 problems from easy functions to more complex stuff.
    I would like less visualization work and a bit more about merge and joins.

    Helpful(0) Unhelpful(0)You have already voted this
  2. Akir Van (verified owner)

    If you ´ve done your online courses, this is your homework. It´s focused on the pandas library and the visualization with matplotlib and seaborne.
    It´s challenging for a new pandas user but I would still recommend it. There ´re plenty of exercises so you really dive in the real use of the most important functions and methods. Not only you learn about pandas but you also practice the data cleaning all data scientists talk about.
    The code is clean and easy to follow.

    Helpful(0) Unhelpful(0)You have already voted this

    Only logged in customers who have purchased this product may leave a review.

    Register New Account
    Shopping cart