Found 19 repositories(showing 19)
thediaryofmos
No description available
vikyale
Python Data Science Toolbox (Part 1) from Datacamp :)
Ranveer-Oshan
No description available
naidaire
DataCamp - Python Data Science Toolbox (Part 1)
No description available
Datacamp course, contained in Python Fundamentals, and Data Scientist with Python Tracks
AnkitaDeshmukh
No description available
ST-Analytics
No description available
No description available
hamdi-trikii
No description available
Creativerrr
GitHub Desktop tutorial repository
DataCamp Data Scientist with Python Career Track Course 3
vladimirbelsch
No description available
It's time to push forward and develop your Python chops even further. There are tons of fantastic functions in Python and its library ecosystem. However, as a data scientist, you'll constantly need to write your own functions to solve problems that are dictated by your data. You will learn the art of function writing in this first Python Data Science Toolbox course. You'll come out of this course being able to write your very own custom functions, complete with multiple parameters and multiple return values, along with default arguments and variable-length arguments. You'll gain insight into scoping in Python and be able to write lambda functions and handle errors in your function writing practice. And you'll wrap up each chapter by using your new skills to write functions that analyze Twitter DataFrames.
sakhan-1111
DataCamp-Python-Data-Science-Toolbox-Part-1
LadyWinterD
No description available
Christo-disc0
Python Data Science Toolbox (Part 1) - final exercise
No description available
Mahnoor-Rana
Project The Android App Market on Google Play Project Description Mobile apps are everywhere. They are easy to create and can be lucrative. Because of these two factors, more and more apps are being developed. In this project, you will do a comprehensive analysis of the Android app market by comparing over ten thousand apps in Google Play across different categories. You'll look for insights in the data to devise strategies to drive growth and retention. This project lets you apply the skills from Manipulating DataFrames with pandas and Python Data Science Toolbox (Part 1). We recommend that you take those courses before starting this project. The data for this project was scraped from the Google Play website. While there are many popular datasets for Apple App Store, there aren't many for Google Play apps, which is partially due to the increased difficulty in scraping the latter as compared to the former. The data files are as follows: apps.csv: contains all the details of the applications on Google Play. There are 13 features that describe a given app. user_reviews.csv: contains 100 reviews for each app, most helpful first. The text in each review has been pre-processed and attributed with three new features: Sentiment (Positive, Negative or Neutral), Sentiment Polarity and Sentiment Subjectivity. Project Tasks Google Play Store apps and reviews Data cleaning Exploring app categories Distribution of app ratings Size and price of an app Relation between app category and app price Filter out "junk" apps Popularity of paid apps vs free apps Sentiment analysis of user reviews
All 19 repositories loaded