There are 1 repository under data-frames topic.
Data quality assessment and metadata reporting for data frames and database tables
Stata-like toolkit for data wrangling on Julia DataFrames
Downloading, analyzing and visualizing CrossFit data
R COBOL DI (Data Integration) Package : Import COBOL CopyBook data files directly into R as properly structured data frames.
Extract, Transform and Load Databases
Repository of DataCamp's "Introduction to R" course.
This repository is for learning most important concepts of Python to start Machine Learning and Deep Learning basics.
Welcome to R for Data Science Repository. It includes the code in R required for dealing with matrices, data frames and creating beautiful visualizations.
In this repository, I've added all the classes regarding Pandas that I've covered at SMIT
An R package for list comprehension
Have you always wanted to make visuals of pokemon data? I found a csv file that has stats on most of the pokemon and I used python, seaborn and matplotlib to make some cool visualizations. This work was sampled from a cool tutorial on seaborn's great visualizations(https://elitedatascience.com/python-seaborn-tutorial#step-1). This covers a good summary of Seaborn’s strengths. In practice, the “well-defined set of hard things” includes: Using default themes that are aesthetically pleasing, making attractive statistical plots, visualizing information from matrices and data frames. I have included the work in a jupyter notebook file and the csv file that has the pokemon data used for this side project.
A query language for Python pandas Data Frames (currently Python)
Python Portfolio For Data Analysis
This repository encompasses various data frames cleaning, transformation, visualization, and machine learning implementations in R language.
Shaun's Python Repository
Project to predict production quantities for a given dataset using Machine Learning algorithms.
high speed client-side data manipulate and filter for high dimension data frames
This repository contains exercises from "Programming for Data Analysis" course from the first semester of my master's studies.
Machine Learning - Regressão Linear.
My beginner to intermediate Python projects.
Convert CSV into data frames to then analyze different statistics within schools in a certain district. There are several different summaries that were created to find what types of schools and in which district had better scores based on spending and other factors. The final result was that spending didn’t necessarily result in higher test scores, but charter schools had a much higher passing rate than public schools.
D-Lab's 1.5 hour foray into R basics for the Haas MBA 200 course.