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
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.
Explore Diwali Sales Data Analysis: a project dissecting 11,251 records with 15 columns to uncover customer demographics and buying trends during the festive season. The objective? Understand customer behavior, identify key demographics and product categories driving sales. Utilizing Python libraries like Pandas, NumPy, Matplotlib, and Seaborn, thi
Extensively worked on data cleaning and data wrangling to analyze the number of deaths between years 2000-2023 with the help of pie charts, bar charts, word cloud and heat maps. Used time series analysis to check if the events of death follow stationarity and forecasted the trends.
This folder contains work I submitted as part of the technical interview for a data science position at CEMA
A set of handy functions for digital data analysis purposes
SQL and dplyr queries; basic descriptive statistics mapping
Mini Project - Concentrating on Pivoting of data tables and Data Wrangling.
This is a pandas test for a data science job. The solution here is in form of a notebook beside the main Python file.
Here I will share my EDA projects using python Language. You can give feedback of my projects. And you can explore your knowledge with that also.
Explore the journey of data wrangling and analysis in the WeRateDogs project. Using Python, gather, assess, and clean data from the Twitter archive of @dog_rates. Unveil insights through visualizations and uncover trends like decreasing retweets over time. For details, refer to wrangle_act.ipynb and wrangle_report.pdf.
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