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Data Science with Python : Full Tutorial 1.2

4 MB / 5+ Downloads / Rating 5.0 - 1 reviews


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Data Science with Python : Full Tutorial, developed and published by AndroFrenzy, has released its latest version, 1.2, on 2020-09-14. This app falls under the Education category on the Google Play Store and has achieved over 500 installs. It currently holds an overall rating of 5.0, based on 1 reviews.

Data Science with Python : Full Tutorial APK available on this page is compatible with all Android devices that meet the required specifications (Android 5.1+). It can also be installed on PC and Mac using an Android emulator such as Bluestacks, LDPlayer, and others.

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App Details

Package name: com.androfrenzy.datascience

Updated: 4 years ago

Developer Name: AndroFrenzy

Category: Education

App Permissions: Show more

Installation Instructions

This article outlines two straightforward methods for installing Data Science with Python : Full Tutorial on PC Windows and Mac.

Using BlueStacks

  1. Download the APK/XAPK file from this page.
  2. Install BlueStacks by visiting http://bluestacks.com.
  3. Open the APK/XAPK file by double-clicking it. This action will launch BlueStacks and begin the application's installation. If the APK file does not automatically open with BlueStacks, right-click on it and select 'Open with...', then navigate to BlueStacks. Alternatively, you can drag-and-drop the APK file onto the BlueStacks home screen.
  4. Wait a few seconds for the installation to complete. Once done, the installed app will appear on the BlueStacks home screen. Click its icon to start using the application.

Using LDPlayer

  1. Download and install LDPlayer from https://www.ldplayer.net.
  2. Drag the APK/XAPK file directly into LDPlayer.

If you have any questions, please don't hesitate to contact us.

Previous Versions

Data Science with Python : Full Tutorial 1.2
2020-09-14 / 4 MB / Android 5.1+

About this app

Data science is the process of deriving knowledge and insights from a huge and diverse set of data through organizing, processing and analysing the data. It involves many different disciplines like mathematical and statistical modelling, extracting data from it source and applying data visualization techniques. Often it also involves handling big data technologies to gather both structured and unstructured data. Below we will see some example scenarios where Data science is used.

Chapters Included

Data Science Introduction
Data Science Environment Setup
Pandas
Numpy
Matplotlib

Data Operations
Data cleansing
Processing CSV Data
Processing JSON Data
Processing XLS Data
Relational databases
NoSQL Databases
Date and Time
Data Wrangling
Data Aggregation
Reading HTML Pages
Processing Unstructured Data
word tokenization
Stemming and Lemmatization

Chart Properties
Chart Styling
Box Plots
Heat Maps
Scatter Plots
Bubble Charts
3D Charts
Time Series
Geographical Data
Graph Data

Measuring Central Tendency
Measuring Variance
Normal Distribution
Binomial Distribution
Poisson Distribution
Bernoulli Distribution
P-Value
Correlation
Chi-square Test
Linear Regression

App Permissions

Allows applications to open network sockets.
Allows applications to access information about networks.