I use Python, and Python libraries (Pandas, NumPy, Matplotlib, Seaborn, BeautifulSoap..etc).
I analyze data and I answer specific research questions.
I present results in histograms, scatter plots, bar plots, pie plots, box plots and multivariate plots (simple linear regression).
I surely can help you with any of the phases below.
I can help you with all the phases if you so require.
I report on each phase and discuss the findings with you, before moving to the next phase.
- Gathering data from multi sources:
- File types like csv, tsv, txt, html, xlsx (Excel), json (objects & arrays)
- Web page scraping & web API-aided scraping.
- Data Cleaning which includes:
- Leaving or removing or replacing NaN (Not a Number) - missing values.
- Spotting the duplicated records and dropping or keeping them.
- Rearranging data with the column names required (inserting, appending, and removing)
- Merging several sources of data in one consistent worksheet.
- Checking the data types and advising on what better data type to suit your future operation.
- Exploratory Data Analysis EDA: Using histograms, scatter plots, box plots, bar plots
-Measures of Center: Mean, Median, Mode.
- Measures of Spread: Range, Interquartile Range (IQR), Standard Deviation, Variance
- Shape of data distribution: Symmetric, Right Skewed, Left Skewed
- Outliers
- Multivariate correlations and simple linear regression analysis.
- Conclusions with descriptive analysis.
- Excel Sheets (.xlsx)
- Flat files (.csv or .tsv)
- Jupyter Notebook: (.ipynb) – or presented in .html file or .pdf file.
Specialties:
Statistical Data Analysis | Python | Data Wrangling | Pandas | NumPy |Matplotlib |Jupyter Notebook |
Data Science | Statistical Analysis | Data Extraction |Beautiful Soup | Exploratory Data Analysis | API
Academic:
MBA in Global Marketing, Startup Management, Project Management (PMP), Engineering (Mechanical)