Data analyst udacity github. txt' file, but it is recommended to use anaconda. Contribute to CaelumIO/Data-Analyst development by creating an account on GitHub. My work should be a reflection of the theory and practice of data visualization, such as visual encodings, design principles, and effective communication. At Github Profile Udacity Nanodegree Projects Intro to Machine Learning Machine Learning - Enron Project Utilized Sklearn to analyze public Enron dataset and build a person of interest identifier. " Learn more About A collection of data analysis. Dirty data refers to missing, dupicates or incorrect data. Convey A portfolio of my work in the Programming for Data Science & Data Analyst NanoDegree programs at Udacity. I chose the Prosper Loans dataset, for this exploratory and explanatory data analytics project. Nanodegree Link: Contribute to MarwaQabeel/Udacity-Data-Analyst-Nanodegree development by creating an account on GitHub. Content for Udacity's Data Analyst curriculum. The analysis is a standard statistical z-test to compare two populations as well as a numerically simulated version of the statistical z-test. A portfolio of my work in the Programming for Data Science & Data Analyst NanoDegree programs at Udacity. Complete collection of Udacity exams for the data analyst nanodegree. Messy data refers to data having different format. ipynb) as well as html files genereted from these. In this analysis, I mostly focus on wrangling WeRateDogs's . Language of instruction was primarily Python and R. This repository contains the full code, datasets and the report for the Data Wrangling process I undertook in Project 2 of the Udacity Data Analyst Nanodegree The Data Wrangling Project I undertook revolves around the Twitter Account "WeRateDogs", an account for rating dogs based on their various features. This is a two part work. Gather data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. Contribute to udacity/data-analyst development by creating an account on GitHub. Data Wrangling Learn the data wrangling process of gathering, assessing, and cleaning data. This project demonstrates the importance and value of data visualization techniques in the data analysis process. I began the Udacity Data Analyst Nanodegree program in January 2023, and this repository includes the associated program outline and project files. The Udacity Data Analyst Nanodegree - Project III. Udacity Data Analyst Nanodegree - Project IV. I have been working recently in merging and analyzing my company’s sales/user data. h. It also does not include publicly available data sets cited and used This repository contains the full code, datasets and the report for the Data Wrangling process I undertook in Project 2 of the Udacity Data Analyst Nanodegree The Data Wrangling Project I undertook revolves around the Twitter Account "WeRateDogs", an account for rating dogs based on their various features. Udacity Data Analyst Nanodegree - Project III. In this Nanodegree Program we're using Python, SQL, and statistics to uncover insights, communicate critical findings, and create data-driven solutions. This project was completed as part of Udacity's Data Analyst Nanodegree. About Solutions for my Udacity's Data Analyst nanodegree program python jupyter-notebook data-analysis udacity-nanodegree Readme Udacity-Data-Analyst-Nanodegree-Project-3 Here, I worked to understand the results of an A/B test run by a hypothetical e-commerce website. Udacity Data Analyst Nanodegree certificate Data-Analyst-Nanodegree-Program Udacity nanodegree. Contribute to beery4010/Communicate-Data-Findings development by creating an account on GitHub. The project deals with introduction to data analysis. I create a data visualization using Tableau that tells a story or highlights trends or patterns in a data set. The project does not include resources (esp. CSV files) provided by Udacity for this course. Jun 7, 2018 ยท python json machine-learning udacity r statistics numpy sklearn pandas data-visualization data-analysis data-wrangling tableau descriptive-statistics data-analyst-nanodegree Updated on Jun 7, 2018 HTML This readme file will serve to answer the Project Submission for the interview Practice of Udacity's Data Analyst Nanodegree. Contribute to beery4010/Analyze-AB-Test-Results development by creating an account on GitHub. Contribute to beery4010/Wrangle-and-Analyze-Data development by creating an account on GitHub. Learn how to apply inferential statistics and probability to important, real-world scenarios, such as analyzing A/B tests and building supervised learning models. Projects for the Udacity Data Analyst NanodegreeP4: Communicate Data Findings Use Python visualization libraries to systematically explore a selected dataset, starting from plots of single variables and building up to plots of multiple variables. Projects from Udacity's Data Analyst program. Learn how to use Python to wrangle data programmatically and prepare it for deeper analysis. Document your wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations using Python. Examples and solutions for project 2 of the Udacity nanodegree program Data Analyst. Each folder is a project and contains some jupyter notebook files (. - WJTownsend/udacity-portfolio Add this topic to your repo To associate your repository with the udacity-data-analyst-nanodegree topic, visit your repo's landing page and select "manage topics. You will use Python visualization libraries to systematically explore a selected dataset, starting from plots of single variables and building up to plots of multiple variables. This repository contains all of my core and optional projects done for Udacity’s Data Analyst Nanodegree (short: DAND) programme. Produce a short presentation that illustrates interesting properties, trends, and relationships that you discovered in your selected dataset. Question 1 - Describe a data project you worked on recently. Udacity's Data Analyst Nanodegree program outline and project files. other data files format: Pillow for image files i. Choose one of Udacity's curated datasets, perform an investigation, and share your findings. non relational database: mongoDB, Json vs Bson Gathering data set using different methods Assessing data There are two main data issues: dirty data and messy data. Necessary libraries can be installed using the 'Requirements. WeRateDogs is a Twitter account that posts and rates pictures of dogs. These ratings often are not serious and have numerators that are greater than the denominators. Exploratory Data Analysis with R Red wine quality EDA This repository contains the full project code for the Udacity Data Analyst Nanodegree Project 3. Udacity Data Analyst Nanodegree - Project V .