The dataset that I scraped can be used as a reference for you. For example, here I do an analysis of the data using Named Entitiy Recognition (NER) from Spacy. I do a supervised learning for clustering sentiment analysis.
Tools used :
Python, pandas, re, TextBlob, Spacy.
Category :
Analysis, visualisasi, EDA
Analysis and visualization of the Uber New York Data obtained from Kaggle.
Tools used :
Python, pandas, numpy, matplotlib, seaborn
Category :
Analysis, visualisasi, EDA
Analysis and visualization of the Netflix data obtained from Kaggle.
Tools used :
Python, pandas, numpy, matplotlib, seaborn
Category :
Analysis, visualisasi, EDA
Exploratory data analysis of New York Airbnb open data. Visualisation using piechart, barchart, histogram, boxplot. Analytic using correlation to predict the price.
Tools used :
Python, Numpy, Pandas, Matplotlib, Seaborn,
Category :
Statistics, EDA, Linear Regression, Visualisation
Dig up covid19 timeseries data from one of the available open fires using Python. Scraping data from API to analysis and visualisation.
Tools used :
Python, json, numpy, requests, pandas, matplotlib, datetime
Category :
Scraping, Timeseries, Statistics, EDA, Visualisation.
Dig up covid19 in Indonesia timeseries data from one of the available open fires using R. Scraping data from API to analysis and visualisation.
Tools used :
R, httr, resp, ggplot2
Category :
Scraping, Timeseries, Statistics, EDA, Visualisation.
Analyzes a dataset of the global average sea-level change since 1880. This project use the data to predict the sea-level change through year 2050.
Tools used :
Python, Pandas, Matplotlib, Seaborn, Scipy.
Category :
Analysis, Visualisation, Regression.
This project visualizes time series data using a Line Chart, Bar Chart, and Box Plots.
Tools used :
Python, Pandas, Matplotlib, Seaborn.
Category :
Analysis, Visualisation.
Visualizes and make calculations from medical examination data using python visualizing tools. The dataset values were collected during medical examinations.
Tools used :
Python, Matplotlib, Seaborn, and Pandas.
Category :
Analysis, Visualisation, Statistics, Correlation.
Analyze demographic data using Pandas. The dataset of demographic data that was extracted from the 1994 Census database. The output to get demographic information.
Tools used :
Python, Pandas, Numpy.
Category :
Analysis, Statistics, EDA.
Data science enthusiast with a strong physics background and experience using Python and R to build statistical modeling, machine learning, data mining, unstructured data analytics to solve challenging business, marketing, and medical problems. Previously I went to Universitas Gadjah Mada. Experienced Contributing Writer about data science and data analytics to Medium Publication. I am a fast learner who likes to challenge myself by participating in data science competitions and active as a competition contributor in Kaggle.