https://github.com/rapter1990/udacity-data-analyst-nanodegree
Udacity Data Analyst Nanodegree Projects
https://github.com/rapter1990/udacity-data-analyst-nanodegree
csv data-analyst-nanodegree data-wrangling python udacity
Last synced: about 2 months ago
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Udacity Data Analyst Nanodegree Projects
- Host: GitHub
- URL: https://github.com/rapter1990/udacity-data-analyst-nanodegree
- Owner: Rapter1990
- Created: 2020-01-15T09:34:00.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2021-01-13T22:32:51.000Z (over 5 years ago)
- Last Synced: 2025-03-14T03:45:03.100Z (over 1 year ago)
- Topics: csv, data-analyst-nanodegree, data-wrangling, python, udacity
- Language: Jupyter Notebook
- Homepage:
- Size: 68.3 MB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Data Analyst Nanodegree By Udacity
This repo holds all the projects have done for the Udacity Data Analyst Nanodegree.
Following are the projects within it:
Following are the projects within it:
## 1. [Weather Trends Exploration](https://github.com/Rapter1990/Udacity-Data-Analyst-Nanodegree/tree/master/P1_Explore_Weather_Trends): Create and explore one visual.
* Program which I used: Jupyter Notebook
* Language which I used : SQL,Python
* Libraries which I Used: Numpy, Pandas, Matplotlib, Seaborn
* Statistic Techniques which I used: Moving averange, mean, Linear Regression
### Repository Contents
This repository contains the following files:
1. A CSV file containing global temperature data;
2. A CSV file containing a subset of temperature data for the Ankara/Turkey, my Hometown;
3. A CSV file containing the list of cities
4. A ipynb file containing my project;
5. The PDF file containing my project report based on what I've done.
## 2. [Investigate A Dataset](https://github.com/Rapter1990/Udacity-Data-Analyst-Nanodegree/tree/master/P2_Investigate_A_Dataset): How has world trend been changed over 200 years in terms of population, life expectancy, fertility,income per person in each country.
* Program which I used: Jupyter Notebook
* Language which I used : Python
* Libraries which I Used: Numpy, Pandas, Matplotlib, Seaborn
* Techniques which I used: Data Wrangling, Data Cleaning, Data Merging, Visualtization
### Repository Contents
This repository contains the following files:
1. A CSV file containing total fertility per woman with respect to each country;
2. A CSV file containing income per individaul with respect to each country;
3. A CSV file containing life expectancy with respect to each country
4. A CSV file containing total population with respect to each country
5. A ipynb,html and pdf file containing my project;
## 3. [Analyze A/B Test Results](https://github.com/Rapter1990/Udacity-Data-Analyst-Nanodegree/tree/master/P3_Analyze_AB_Test): Analyze A/B Test Results
* Program which I used: Jupyter Notebook
* Language which I used : Python
* Libraries which I Used: Numpy, Pandas
* Techniques which I used: Data Wrangling, Data Analytics, Logistic Regression, Practical Statistic
### Repository Contents
This repository contains the following files:
1. A CSV file containing A/B dataset;
2. A CSV file containing edited A/B dataset;
3. A CSV file containing countries information
4. A ipynb, file containing my project;
## 4. [Wrangle and Analyze Data](https://github.com/Rapter1990/Udacity-Data-Analyst-Nanodegree/tree/master/P4_Wrangle_And_Analyze_Data): WeRateDogs
* Program which I used: Jupyter Notebook
* Language which I used : Python
* Libraries which I Used: Numpy, Pandas
* Techniques which I used: Data Gathering, Data Assessing, Data Cleaning, Data Wrangling, Visualtization
### Repository Contents
This repository contains the following files:
1. A CSV file containing WeRateDogs Twitter archive;
2. A TSV file deriving from https://d17h27t6h515a5.cloudfront.net/topher/2017/August/599fd2ad_image-predictions/image-predictions.tsv as tweet image predictions;
3. A Text file named for tweet_json.txt getting values from WeRateDogs Twitter archive csv with tweepy and Twitter API
4. A Text file named for tweet-json.txt getting values from WeRateDogs Twitter archive csv file without tweepy and Twitter API
5. A ipynb, file containing my project;
6. Twitter API Information
consumer_key = "UnbSXP1KKBRB1kkx5Ry4Yfezi"
consumer_secret = "k9JoR24jMc09Ikl9IPurim8tCsKQNSvSvsw3SgfhO14h3vQwZ9"
access_token = "411318653-hFPRaoKqZ0IlCN1nGI4KED7oalEVbak1wKKflBBW"
access_secret = "zhyKTfCcFHIH4Gh3C2d2n1svZe6zf9OsXeSQJ704a5lD2"
## 5. [Communicate Data Findings](https://github.com/Rapter1990/Udacity-Data-Analyst-Nanodegree/tree/master/P5_Communicate_Data_Findings): Bay Wheels Analysis (older name : Ford GoBike)
* Program which I used: Jupyter Notebook
* Language which I used : Python
* Libraries which I Used: Numpy, Pandas
* Techniques which I used: Data Gathering, Data Assessing, Data Cleaning, Data Wrangling, Visualtization
### Repository Contents
This repository contains the following files:
1. A CSV file containing baywheels tripdata in Janunary 2020;
2. A CSV file containing clean baywheels tripdata after the process of data gathering , data Assessing, data Cleaning;
3. readme file giving detailed information about the project;
4. output_toggle.tpl file exporting your slide deck and containing extra functionality to the slide deck by hiding the code to start, only making it visible if the reader clicks on the output which should mostly be visualizations in the case of this project;
5. An exploration ipynb file containing my project;
6. A slide deck ipynb file providing how the slide deck should be organized and including pre-set slideshow settings;
7. An exploration html file containing my project;
8. A slide deck html file providing how the slide deck should be organized and including pre-set slideshow settings;
9. To view the slide deck, this command is used as shown below
jupyter nbconvert slide_deck.ipynb --to slides --template output-toggle.tpl
--post serve
# Data Analyst Nanodegree Certificate
