The rapidly growing world of today is expanding technology at a rate like never before. Though people may have ways to collect data, when it comes to extracting conclusions insights with it, there still exists a strain on the head. So, data visualization charts like bar charts, scatterplots, line charts, geographical maps, etc. are extremely important. They show you information just by looking at them which normally you would get by reading text reports or spreadsheets to understand the data.
Below is a list that compiles the top libraries for great data visualization. Let’s quickly get into understanding these libraries:
1) Seaborn
2) Plotly
3) Matplotlib
4) Altair
5) D3.js
There are several kinds of graphs that you can plot through Python and its various libraries. You should begin with Matplotlib if you are new to Python data visualization.
For visit - 9 Interactive Python Libraries for Visualizing Data
Traders used these graphics to decide where to invest their money and use them for technical analysis.
For example, they could tell when an asset was undervalued or overpriced because they had seen similar patterns before.
The history Coin charts were first popularized by Charles Dow.
They show the pattern of price movements over time, allowing investors to find ways that can help them predict where an asset will be in the future.
Charting allows investors to predict where the market is headed.
The history of coin charts and technical analysis goes back well over a hundred years ago.