This repository contains projects that have been done for Practicum Yandex100 training program by Natalie Ulfskiy.
I’m a natural analyst graduated from Yandex100, a 9-month intensive online exclusive program designed to train 100 talents to be successful Data Analysts.
These projects are to verify that I have developed a solid foundation of descriptive and predictive statistics, Exploratory Data Analysis, Data Collection and Storage, Machine Learning, hypothesis testing and storytelling with data.
I have been taught to clean and organize data, uncover patterns and insights, draw meaningful conclusions, and clearly communicate critical findings.
As a critical thinker with a B.A. in Economics, I make it my mission to immerse myself in all aspects of what makes a business grow in the smartest possible way.
List of projects:
| Project name | Description | Libraries used |
|---|---|---|
| AB testing | to gange hypothesis, analyse hypotheses and results of A/B testing. | pandas, plotly.express, plotly, matplotlib.pyplot, matplotlib, numpy, seaborn |
| Games and platforms | Identifing patterns that determine whether a game succeeds or not. Creating a user profile for each region. Testing statisical hypotheses. | pandas, matplotlib.pyplot, numpy, functools, stats, numpy, seaborn, squarify, plotly |
| Taxi market | Aim of the project is to find patterns in the available data to define passenger preferences and impact of external factors on rides. Testing hypothesis about the impact of weather on ride frequency. | pandas, plotly.express, matplotlib.pyplot, numpy, scipy, seaborn, squarify |
| Marketing expences analysis | to analize and optimize marketing expenses of Yandex.Afisha. We are going to look into data related to site visits, orders and costs from June 2017 through May 2018. | pandas, plotly.express, matplotlib.pyplot, numpy, scipy, seaborn |
| Restaurant market analysis | market research of an open-source data on restaurants in LA with the purpose to open a small robot-run cafe in Los Angeles. The main aim is to study the current market conditions. Presentation | pandas, IPython.display, plotly.express, plotly, matplotlib.pyplot, matplotlib, numpy, scipy, seaborn, re, usaddress, sys, warnings |
| Sales funnel | to investigate user behavior for the company’s app (a startup that sells food products). First we will preprocess the data and study the sales funnel: find out how users reach the purchase stage, how many users actually make it to this stage, how many get stuck at previous stages. Next we will check the results of an A/A/B test: if change of the fonts for the entire app have any impact on users. We will pick up the equal number of users for all 3 groups and run a statistical test to check if there is a statistically significant difference in number of users for any of the events. | pandas, IPython.display, plotly.express, plotly, matplotlib.pyplot, matplotlib, numpy, scipy, seaborn, math, sys, warnings |
| Trending youtube videos | analyze trending-video history on YouTube Tableau dashboard | sqlalchemy |
| Gym churn prediction model (ML) | The aim of the project is to develope a customer interaction strategy based on analytical data for gym chain Model Fitness. We will develope a model for predicting the probability of churn (for the upcoming month) for each customer. | pandas,IPython.display, plotly.express, plotly, matplotlib, numpy, median, scipy, seaborn, math, plotly.subplots, sklearn, scipy |
| Phone operators analysis | Study of effectivness of phone operators for a virtual telephony service. Tableau dashboard | pandas, IPython.display, scipy, matplotlib, numpy, functools, stats, seaborn, math, plotly |
For more information please visit my Linkedin profile