Shulou(Shulou.com)06/01 Report--

What are the common chart types of Python data visualization? most people do not understand the knowledge points of this article, so the editor summarizes the following contents, detailed contents, clear steps, and has a certain reference value. I hope you can get something after reading this article, let's take a look at this "Python data visualization commonly used chart types have what" article.

The purpose of data visualization is to make the data reflect the data situation more efficiently, so that readers can read it more efficiently, not just for their own use, to highlight the laws behind the data through data visualization, so as to highlight the important factors in the data, and, data visualization can make data more intuitive.

The role of visualization using chart data

There are three main functions of using charts to show data:

Visualization of expression: the use of charts can turn lengthy into concise, abstract into concrete, esoteric into images, making it easier for readers or listeners to understand themes and ideas. Highlight the point: through the special setting of information such as the color and font of the data in the chart, the focus of the question can be effectively transmitted to the reader or audience. Reflect specialization: appropriate and decent charts convey the professional, dedicated and trustworthy professional image of the cartographer. Professional charts will greatly enhance one's competitiveness in the workplace, add points to personal development, and create opportunities for success.

A chart is a visual display of data. Exquisite charts can facilitate users to interpret the relationship between numbers. Compared with boring tables, they help to find trends and rules that are easy to be ignored. Through the analysis of trends and rules, we can help users to make a correct judgment. We classify the commonly used chart types as basic charts and advanced visual charts.

Basic chart

Bar chart, line chart, pie chart, bar chart, area chart, scatter chart, stock price chart, radar chart, bubble chart, surface chart, combination chart, etc.

Advanced visual chart

Tree diagram, rising sun map, histogram, arrangement diagram, box diagram, waterfall diagram, funnel map, Map map, dynamic chart, etc.

1. Column chart

Bar chart is one of the most common basic charts in Excel. Column charts are usually used to show the differences between different items in a series or between different items in multiple series, which are distinguished by the color of the columns. Each data point is represented by a vertical column, and the height of the column represents the size of the value. The horizontal axis is generally classified items, and the vertical axis is the corresponding value of different items.

two。 Line chart

The line chart connects the data points of the same series with lines, and the fluctuation of the broken line is used to indicate the increase and decrease of the data. Line chart is more suitable for drawing continuous data, from which we can find the law of data trend.

3. Pie chart

When analyzing the proportion of each value in a set of data, the pie chart is the best choice. Pie charts can only use one data series. When there are too many data points in the same series, the pie chart will not be able to clearly explain the information to be expressed. Therefore, it is recommended that there are no more than 6 data points.

4. Area map

An area chart is equivalent to a graph filled with colors under a line chart, and the area chart pays more attention to the relationship between data categories over time.

5. Scatter plot

Scatter diagram refers to the distribution of data points on the plane of Cartesian coordinate system, which can be used to observe the relationship between two variables.

6. Radar chart

Radar map, also known as Dabatu, spider web chart, is a chart that can represent multiple classified data sizes. It maps multiple classified data to corresponding axes, which start at the same center point and usually end at the edge of the circle. Connecting the same group of points with lines is called radar map.

7. Tree view

The tree view is more suitable for hierarchical data, and the tree view represents the data points as rectangular. the larger the value, the larger the rectangular area, which is suitable for the case of large amount of data, especially more categories. Such as the SKU of all kinds of e-commerce.

8. Histogram

The histogram is used to show the distribution of data in different groups, and the frequency distribution is represented by the height of the column. according to the display results of the histogram, users can directly see the data distribution, the location of the center and the degree of discretization of the data.

9. Box diagram

Box chart, also known as box chart, box chart or box chart, contains the maximum, minimum, average, median and two quartiles of a set of data. The biggest advantage of box chart is that it is not affected by outliers (outliers are also known as outliers). It can describe the discrete distribution of data in a relatively stable way, which is convenient for observers to analyze data quickly.

10. Funnel chart

The funnel chart is mainly used to analyze the transformation of each step in a multi-step process, and we can find the important loss of users in a series of operations.

11.Map map

Map maps can draw single-layer data or multi-layer data (mixed layers), the relationship between data and space. Geographical maps can be drawn not only through the numerical measurement of longitude and latitude, but also through the category dimensions of provinces and cities.

The above is about the content of this article on "what are the common chart types of Python data visualization?", I believe we all have a certain understanding. I hope the content shared by the editor will be helpful to you. If you want to know more related knowledge, please pay attention to the industry information channel.

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.