Buxfer is a top rated money management and tracking tool that helps its users with their budgeting, retirement planning, investments, forecasting, and more. Buxfer can sync with over 20,000 banks and other financial institutions from over 110 countries to ensure you can track all your financial transactions in one place. Users get access to detailed insights, showcasing their spending trends, and sending real-time alerts on spending limits set for your accounts.
Based on our record, Plotly seems to be a lot more popular than Buxfer. While we know about 30 links to Plotly, we've tracked only 1 mention of Buxfer. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I know it may seem like that but you definitely can. My wife and I lived off of 35k for about 8 months. Our rent was $800 and our bare minimum after that was about $500, so $1,300 in total (a little more than half her monthly income but we did go out every now and then). During that time I was getting my business up and running and I am so grateful for her hard work. During those months we budgeted like crazy. We... Source: almost 3 years ago
How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / 3 days ago
For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: 6 months ago
If your CEO wants you to solo build an alternative to Tableau, PowerBi, or even Plotly then consider him/her delusional. Source: about 1 year ago
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: about 1 year ago
I use plotly and like it a lot. It is slower though. Noticeable if you want to batch-generate a bunch of images and dump them into a folder. But that probably isn't the case most times. Source: about 1 year ago
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