Data Wrangling Assignments with pandas

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$9.95

Data Wrangling Assignments with pandas
Data Wrangling Assignments with pandas

$9.95

Description

DATA WRANGLING PRACTICE PROJECT WITH PANDAS AND NUMPY

 

INSTRUCTOR
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.

PROJECT DESCRIPTION
The aim of this project is to replicate the tasks every data anaylist 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.

DOWNLOAD / CONTENT
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.

WHAT YOU WILL PRACTICE
– 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 assigments related to:
– Import/export  gzip, csv and Excels.
Remove, select, rename, filter columns and rows.
– Nulls
– Data types.
– Groupby
– Filters
– Outliers and duplicates.
– Basic Regex.
– Date formats.
– Data engineering.
– Numpy
– One hot encoding.
– Merge and joins.
– Loops (for).
– Visualization: boxplot, bars, countplot, scatterplot, heatmaps, pairwise, etc.

VERSION
Python 3.7
Pandas: 0.24.2
Numpy: 1.16.4

 

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

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Additional information

Specification: Data Wrangling Assignments with pandas

Difficulty
Time Estimate 1 Day
File PDF, Other

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