An introductory workshop on pandas with notebooks and exercises for following along. Slides contain all solutions.
Jupyter Notebooks with different purposes: Social Network WebScrapping, ETL, Selenium WebDriver for Web Testing, Automation using Python, Data Wrangling, Data Transformation, Data Cleaning, Stock Market Analysis, APIs, Machine learning Algorithms, etc...
A Jupyter Notebook collection designed to develop a practical understanding of Machine Learning Operations (MLOps) defined in the NESA Software Engineering Course Specifications pg 27.
PySpark (Python for Apache Spark) Essentials - Wrangling Big Data for Machine Learning.
Inspecting the quality of isobaric labeling proteomic data in a Jupyter notebook. Data output from Proteome Discoverer.
Data parsing with pandas in jupyter notebook.
Notebooks with some EDA and Machine Learning Models
Repo containing Jupyter notebooks with practice projects from DataCamp
Descriptive statistics of life expectancy in Southeast Asia using Jupyter Notebook
Data Wrangling OpenStreetMap Milwaukee data with sqlite3 in iPython/Jupyter Notebook
Azure Databricks notebook sample to connect Blob Storage of Azure Log Analytics
Data wrangling of Austin OpenStreetMap data using Python, PyMongo, MongoDB, and Jupyter Notebooks.
Contains labs in Jupyter Notebooks created as part of my IBM Data Science Professional Certificate
This is demo repo to demonstrate how to leverage Azure Text Analytics to perform Personally identifiable information (PII) data scrubbing by Python (Jupyter Notebook). This is important part of data wrangling/data cleaning.
This Jupyter notebook shows how average level of U.S. Senate representation varies with race and ethnicity.
This repository showcases my data science skills, including EDA, Python, data cleaning/wrangling, and visualization. It demonstrates my problem-solving abilities through interactive insights. Explore the notebooks and provide feedback.
This repository includes Jupyter notebooks focused on analyzing data from SpaceX Falcon 9 rocket launches. The project covers the entire data science process, from data collection and preparation to exploratory analysis and machine learning predictions. Each notebook addresses a distinct step in the analysis workflow.
A Jupyter Notebook with the analysis for a Whatsapp Chat using several techniques of data wrangling, EDA and Sentiment Analysis
A Jupyter Notebook where I wrangle some data and plot a chart to draw some conclusions about a user's Spotify history
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