Portfolio of data analytics projects
| № | Project name | Sphere | Description | Stack |
|---|---|---|---|---|
| 1 | Borrower Reliability Study | Finance | Data preprocessing and analysis; lemmatization; exploratory data analysis | Python pymystem3 Pandas NumPy |
| 2 | Research of advertisements for the sale of apartments | Real estate | Data preprocessing; search for correlations | Pandas Matplotlib NumPy |
| 3 | Determination of a prospective tariff for a telecom company | Telecom | Combining data from five tables into one; studying anomalies in data; exploratory data analysis; statistical data analysis | Pandas Matplotlib display math NumPy SciPy Statsmodels |
| 4 | Video game market research | Game industry | Data preprocessing; data analysis; compiling a portrait of users in each region; hypothesis testing; identifying the parameters that determine the success of video games in different regions of the world; preparation of a report for the purpose of planning advertising campaigns for a computer games store | Matplotlib Pandas Python NumPy SciPy downcast warnings |
| 5 | Unit economics of a mobile application | Mobile App | Calculation of economic indicators (metrics of unit economy); evaluation of return on investment in marketing; search for a "bottleneck" in the economic model; cohort analysis | Pandas Matplotlib NumPy Seaborn |
| 6 | Hypothesis Prioritization and A/B Test Evaluation | Mobile App | Prioritization of hypotheses by ICE and RICE frameworks; evaluation of A/B testing results; charting: cumulative revenue, average check, conversion by groups; calculation of statistical significance of differences in conversions and average checks based on raw and cleaned data | Matplotlib Pandas Python Seaborn NumPy SciPy math |
| 7 | The food service market | Catering | Data preprocessing; exploratory data analysis; preparing a presentation | Pandas Seaborn Matplotlib Numpy re Requests io API |
| 8 | Event analytics of the mobile application | Mobile App | Description of the funnel of events (from the first launch to purchase); search for the difference between client and user sessions; cohort analysis; A / A / B-test | Pandas Seaborn Matplotlib plotly math NumPy SciPy warnings |
| 10 | Music preference research | Internet service | My first research project in python | Pandas |