Data wrangling in Python
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Updated
Apr 21, 2017 - Jupyter Notebook
Data wrangling in Python
Converting and integrating data from multiple sources is often tricky business. Luckily there are some great tools available that make this a breeze. I use a genetic annotation file (Brachypodium) and incorporate gene ontology definitions. This Uses dplyr and tidyr to do the data wrangling.
You can find the dataset in kaggle
The package reaches out to scientists that seek to estimate MOI and lineage frequencies at molecular markers using the maximum-likelihood framework described in https://doi.org/10.1371/journal.pone.0261889. Users can import data from Excel files in various formats, and perform maximum-likeli
Some materials I used to Train basics of R
Analysis of NOAA storm database with R to determine most severe types of weather event
[Data wrangling, Seaborn visualization] A data science exercise for food safety evaluation in SF
Study project for data wrangling, analysis and visualization from Udacity Data Analyst nanodegree. Tweets from twitter account WeRateDogs are analysed as dataset.
DATA PROFILING is a process of examining, analyzing, and creating useful summaries of data. The process yields a high-level overview which aids in the discovery of data quality issues, risks, and overall trends.
The analysis seeks to understand how the perceptions of schools affect performance and demographics and vice versa
This is an EDA project that explores the Data Science Salaries in 2023 dataset. The purpose of this project is to gain insights into the current trends and patterns of salaries in the data science industry.
This project aims to predict student grades using various independent features. It involves data wrangling, exploratory data analysis, data visualization, and linear regression. The project uses Python and Jupyter notebooks for implementation.
Analyzing and visualizing is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs.
Predicting price and customer satisfaction: Airbnb data
My collection of visualizing different datasets using (Matplotlib, Seaborn, and Folium) packages for Python
Determines the price of the launch. Also, determines if SpaceX will reuse the first stage.
Acest repo conține materiale, seturi de date și soluții care au fost folosite în cadrul Școlii de vară Astra, prima ediție, 2021
Visualising World Mortality Rates
• Applied data wrangling and data visualisation skills on stroke dataset and created visualisations using the R programming language in Rstudio. • Prepared a report using Latex which included a set of decision supports using visualisations • Created a web-based application with interactive graphs (using shiny package from R) to tell a direct story.
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