1,100 skills found · Page 23 of 37
Plavit / EGovernment Index DashboardA simple Python and Dash Plotly app that visualizes hard-to-process data from eGovernment indexes by the European Union and the United Nations
amarchenkova / SnapshotplotGit for Plots. Capture Python plots with the code that created them, automatically.
aditeyabaral / GpythonRecreated the popular graphing application "Desmos" on Python using matplotlib, scipy and numpy. GPython can be used as an extensive graphing application that can plot 2D, 3D and even polar curves and also differentiate and integrate functions.
bitrot-sh / WispyGraphically plot wi-fi traffic using neo4j and python
laurentbbb / PENPLOTTER PAINT SPLITTERA Python GUI tool to split pen plotter drawings into segments with automatic paint reload paths. Perfect for creating paintings with pen plotters.
laurabravo97 / Dynamic Functional Connectivity AnalysisPython script to obtain dynamic functional connectivity metrics, after using a sliding window approach, statistical analyses to test for differences between groups and plots of results using plotly (code available, but output plots the result cannot be displayed on github).
aleponce4 / Libs Spectroscopy WorkbenchPython-based software for controlling ocean optic spectrometers and analyzing Laser Induced Breakdown Spectroscopy (LIBS) data. Features GUI via tkinter. Processes CSV LIBS files, generates plots, and identifies elemental lines.
abhi-9598 / Covid19 Vaccine Visualization Python🦠 Python project for visualizing COVID-19 vaccination data by ZIP code. Includes data cleaning and plots like bar chart, pie chart, heatmap, scatter, and pair plot using Pandas, Matplotlib, and Seaborn. Guided by Baljinder Kaur.
pepprseed / Svgdatashapesa compact set of python functions for creating many types of plots and data displays in SVG for use in web pages.
Himanshu-Kaushik1626 / Data VisualisationA Python project showcasing data visualization using NumPy, Pandas, Matplotlib, and Seaborn. It covers data preprocessing, statistical analysis, and creating insightful visualizations like line plots, heatmaps, box plots, and more. Ideal for learning and practicing data analysis and visual storytelling.
ifsvivek / Plot Arduino Data In Real TimeThis Python code uses the serial library to read data from an Arduino microcontroller, and the matplotlib library to plot the data in real-time. The code continuously reads data from the Arduino and adds it to a list of values that is plotted using matplotlib.
kennedyCzar / NLP PROJECT BOOK INSIGHTS WITH PLOTLYPlotly-Dash NLP project. Document similarity measure using Latent Dirichlet Allocation, principal component analysis and finally follow with KMeans clustering. Project is completed with dynamic visual interaction.
Jai-Agarwal-04 / Sentiment Analysis With InsightsSentiment Analysis with Insights using NLP and Dash This project show the sentiment analysis of text data using NLP and Dash. I used Amazon reviews dataset to train the model and further scrap the reviews from Etsy.com in order to test my model. Prerequisites: Python3 Amazon Dataset (3.6GB) Anaconda How this project was made? This project has been built using Python3 to help predict the sentiments with the help of Machine Learning and an interactive dashboard to test reviews. To start, I downloaded the dataset and extracted the JSON file. Next, I took out a portion of 7,92,000 reviews equally distributed into chunks of 24000 reviews using pandas. The chunks were then combined into a single CSV file called balanced_reviews.csv. This balanced_reviews.csv served as the base for training my model which was filtered on the basis of review greater than 3 and less than 3. Further, this filtered data was vectorized using TF_IDF vectorizer. After training the model to a 90% accuracy, the reviews were scrapped from Etsy.com in order to test our model. Finally, I built a dashboard in which we can check the sentiments based on input given by the user or can check the sentiments of reviews scrapped from the website. What is CountVectorizer? CountVectorizer is a great tool provided by the scikit-learn library in Python. It is used to transform a given text into a vector on the basis of the frequency (count) of each word that occurs in the entire text. This is helpful when we have multiple such texts, and we wish to convert each word in each text into vectors (for using in further text analysis). CountVectorizer creates a matrix in which each unique word is represented by a column of the matrix, and each text sample from the document is a row in the matrix. The value of each cell is nothing but the count of the word in that particular text sample. What is TF-IDF Vectorizer? TF-IDF stands for Term Frequency - Inverse Document Frequency and is a statistic that aims to better define how important a word is for a document, while also taking into account the relation to other documents from the same corpus. This is performed by looking at how many times a word appears into a document while also paying attention to how many times the same word appears in other documents in the corpus. The rationale behind this is the following: a word that frequently appears in a document has more relevancy for that document, meaning that there is higher probability that the document is about or in relation to that specific word a word that frequently appears in more documents may prevent us from finding the right document in a collection; the word is relevant either for all documents or for none. Either way, it will not help us filter out a single document or a small subset of documents from the whole set. So then TF-IDF is a score which is applied to every word in every document in our dataset. And for every word, the TF-IDF value increases with every appearance of the word in a document, but is gradually decreased with every appearance in other documents. What is Plotly Dash? Dash is a productive Python framework for building web analytic applications. Written on top of Flask, Plotly.js, and React.js, Dash is ideal for building data visualization apps with highly custom user interfaces in pure Python. It's particularly suited for anyone who works with data in Python. Dash apps are rendered in the web browser. You can deploy your apps to servers and then share them through URLs. Since Dash apps are viewed in the web browser, Dash is inherently cross-platform and mobile ready. Dash is an open source library, released under the permissive MIT license. Plotly develops Dash and offers a platform for managing Dash apps in an enterprise environment. What is Web Scrapping? Web scraping is a term used to describe the use of a program or algorithm to extract and process large amounts of data from the web. Running the project Step 1: Download the dataset and extract the JSON data in your project folder. Make a folder filtered_chunks and run the data_extraction.py file. This will extract data from the JSON file into equal sized chunks and then combine them into a single CSV file called balanced_reviews.csv. Step 2: Run the data_cleaning_preprocessing_and_vectorizing.py file. This will clean and filter out the data. Next the filtered data will be fed to the TF-IDF Vectorizer and then the model will be pickled in a trained_model.pkl file and the Vocabulary of the trained model will be stored as vocab.pkl. Keep these two files in a folder named model_files. Step 3: Now run the etsy_review_scrapper.py file. Adjust the range of pages and product to be scrapped as it might take a long long time to process. A small sized data is sufficient to check the accuracy of our model. The scrapped data will be stored in csv as well as db file. Step 4: Finally, run the app.py file that will start up the Dash server and we can check the working of our model either by typing or either by selecting the preloaded scrapped reviews.
kanchanchy / Data Visualization In PythonData Visualization in Python using Matplotlib, Seaborn and Plotly Express
leifdenby / Tephigram PythonPython package for plotting tephigrams
cyprienh / Chiplotle3The Chiplotle serial plotter library for Python 3
metno / PysurfexPython API to SURFEX. Tool to create offline SURFEX forcing, SURFEX files, running SURFEX and plot results.
z4ir3 / Derivatives PlaygroundPython tkinter GUI for interactive Black-Scholes option prices/greeks plot
aymeric-spiga / Planetoplota cool python-based tool to plot stuff and explore data
VManuelSM / Membership FunctionsMembership functions for fuzzy logic, encoded and plotted in python.
