ggplot plots

geometry class, drawing the graphic elements in the diagram other types of graphics, such as histograms, box plots, and so on. such as points, lines, polygons, etc., can also be used to draw.The basic parameters inside the above function are the same. Take a scatter chart as an example: Geom_point (mapping=null,data=null,stat= "Identity", position= "Identity", Na.rm=false,...) The parameter mapping is used to build the map, data specifi

Ggplot2R's Graphing toolkit, you can use very simple statements to achieve very complex and beautiful results.QplotLoad Qplot=#1. Visualize by basic classification of Color,size,shape#1.1 Simple scatter plot (using color classification, diamonds of different colors are represented by dots of different colors)#1.2. Simple scatter plots (using shape classification, different cutting methods are represented by different shapes of points)#2. Drawing diffe

The following plots take the Weibull distribution (Weber distribution, Weibull distribution) as an exampleFor Weibull distribution (Weber distribution, Weibull distribution), please refer to my blog http://www.cnblogs.com/wwxbi/p/6141501.htmlLibrary (GGPLOT2)# both D and Y here are in order of sizedYDfGgplot (Df,aes (x=d,y)) +Geom_line (colour= "green") +Ggtitle ("Weibull distribution \ n probability density map")# Here's H no size orderH

glued together by "+" to a layer (layer), so the layer is an important concept in Ggplot2.The following data is a graduate data, from Wang Bin's editor-in-chief of the "Data analysis and R language Modeling" practice data, a total of 48 sample points, 9 attributesOne, dataIn Ggplot2, the accepted data set must be in data.frame format. This format is easy to save data, and can easily change the existing dataset with%+% under the original drawing parameters. The Library ("Ggplot2") #调用包 ug=read.t

obtain the analysis results and the gravel plots respectively. However, the psych extension package is more flexible.1 Select the number of principal componentsThere are usually several criteria for selecting the number of principal components: Choice based on experience and theory Based on the cumulative variance contribution rate, for example, select the number of principal components that contribute to 80% of the cumulative variance.

). Learning pandas you have to master is: Summarize and calculate descriptive statistics, process missing data, hierarchical indexes Clean, transform, merge, reshape, GroupBy technology Date and time data types and tools (date processing easy to fly) See blog: http://www.cnblogs.com/chaosimple/p/4153083.htmlthree. Matplotlib:The most famous drawing system in Python, many other drawings such as Seaborn (for pandas drawings) are also encapsulated by them. John Hunter, a found

Plotnine Csdn's edit and upload picture experience is too bad, more examples to plot-example to see. Https://github.com/has2k1/plotnine-examples Installation website: https://plotnine.readthedocs.io/en/stable/index.html Github:https://github.com/has2k1/plotnine Ggplot2 official website: http://ggplot2.tidyverse.org/reference/index.html#section-plot-basics Conda install-c conda-forge Plotnine # # Use Import pandas as PD import NumPy as NP from plotnine import * from plotnine.data import * Mpg.h

, jpgraph_bar.php files in the./src directory, jpgraph_line.php files, jpgraph_plotmark.inc, and jpgraph. php files to the same directory.2. Create a database jpg and a database table test.Create two fields:ID (primary key): intNumber: intAnd add some data3. Modify example16.2.phpModified codeInclude ("jpgraph. php ");Include ("jpgraph_line.php ");Include ("jpgraph_bar.php "); $ Connect = mysql_connect ("localhost", "root ","");Mysql_select_db ("jpg", $ Connect );$ Query = mysql_query ("select *

Ggplot2 Scale Related SettingsScale settings: Mainly used to adjust settings for each layer after Ggplot drawing.1. Related attribute scale settingIncludes Scale_size (), Scale_alpha (), Scale_shape ()As you can see from the name above, these three settings are primarily related to the Ggplot layer properties, including size, transparency, and shape.The main parameters for this setting are listed below:SCAL

= ProgressBar (maxval=10) for I in range (1, one): Pbar.update (i) Time.slee P (1) pbar.finish () # 60% |######################################################## | 9) Colorama When you print the log with ProgressBar, why not add color to them! In fact, when there is a big mistake, it can give you a quick reminder. Colorama is easy to use. Just write it in your script and add it to the text you want to print: Colorama-red) UUID For me, there are only a few tools that are really needed

Matplotlib, Seaborn, and Ggplot) · Bokeh has the flexibility to use interactive applications, layouts, and different styling options for visualization Combining the advantages of bokeh and its challenges, bokeh is the ideal tool for the rapid development of prototype products. However, if you want to make something new in the context of the product, D3.js may still be your best bet.　　The challenges facing bokeh: As with any upcoming

JavaScript library that makes charts, supporting most of the chart types: line graphs, graphs, area plots, area graphs, histogram, pie charts, scatter plots, etc. The Hplot function is provided in the Rcharts package.The basic principle of hplot drawing is illustrated by taking the student survey data set survery in the mass package as an example. We draw a bubble chart of the student's height and pulse be

the residuals, the model is not strong enough to extract all the signals.Evaluation method:Mean square error (MSE): The average deviation of the forecast can be evaluated, but the MSE is the square of the average deviation valueRMS error (RMSE): The root value of the MSE, but it is not intuitive to see the model is unreasonable, that is, only compare two models which is better, but not alone to evaluate the performance of a modelR2: Evaluate the quality of a single model, with the mean predicti

PrefaceA line chart is typically used to visualize the dependencies of two consecutive variables , where the horizontal axis is often the timeline.But the horizontal axis is not necessarily a continuous variable, it can be ordered discrete variable.draw a basic line chartThis example uses the following test data set:The drawing method is to first call the Ggplot function to select the dataset and indicate the horizontal axis in the AES parameter. Then

Introduction There is no doubt about the quality of the Ggplot2 package, but its drawing grammar is still a little difficult for beginners, Ggplot2: Data analysis and Graphic Art This book also introduces the basic philosophy and operation of Ggplot2 package, and the personal feeling examples are not rich enough, So the use of the package is still stuck at the dabbler level. One day, suddenly found a Ggplot2 package example book, exultation, English name is R Graphics Cookbook, Chinese version i

Draw a simple histogram Problem How to draw a histogram. Method Run the Geom_histogram () function and map a continuous variable to the parameter x (see Figure 6-1): Ggplot (Faithful, AES (x=waiting)) + Geom_histogram () Discuss The Geom_histogram () function requires only one column of the data box or a single data vector as a parameter. Taking the faithful dataset as an example, the dataset contains two columns of information describing the Old

)) +geom_density ()#如, Peak Flat, try to divide data by sexGgplot (Heights.weights, aes (x = Height, fill = Gender)) +geom_density ()#混合模型, a non-standard distribution formed by mixing two standard distributions#正态分布, bell-shaped curve or Gaussian distribution#按性别分片Ggplot (Heights.weights, aes (x = Weight, fill = Gender)) +geom_density () +facet_grid (Gender ~.)#以下代码指定分布的均值和方差, M and s can be adjusted, just move center or telescopic widthM S

package. Watch data wrangling with R via Rstudio. (https://www.rstudio.com/resources/webinars/data-wrangling-with-r-and-rstudio/) Read and practice how to use the Dplyr, Tidyr, and data.table packages. Step five: Effective data visualizationIt is a matter of pride to create your own data visualization work. However, data visualization is both a skill and an art. Many scholars read Edward Tufte's "visual quantitative data" principle, or Stephenfew's "Pitfalls on dashboard Design". Y

chart6. Multiple linear graphsBefore drawing, first talk about the limitations of Ggplot2.The biggest limitation of GGPLOT2 is that it does not support double-coordinate and pie-charts. Even if you can do these graphics, but also a lot of settings, it is very cumbersome to do.According to my own understanding, the root of this limitation is not related to the aesthetic habits and analysis habits of ggplot2 developers Hadley themselves. For details, see his question in StackOverflow: It

% | ##################################### #################### | 9)Colorama Since you have set a good progress bar for logs, why not make them colorful! You can also remind yourself when a serious error occurs. Colorama is super easy to use. Just pop up your script and add any text you want to change the color: 10)Uuid In my mind, we actually only need a few tools for programming: hashing, key/value storage, and the Globally unique Identifier universally unique ids, uuid ). Uuid is built into t