ggplot data

This article mainly introduces three methods to call ggplot in Python. ggplot, as a graphics library, is often used to create a visual view of data, you can refer to the following three methods to call ggplot in Python (IPython Notebook. In the big data era,

Three methods of calling ggplot in Python: pythonggplot This article provides three different methods to call ggplot in Python (IPython Notebook. In the big data era, data visualization is a hot topic. Every BI manufacturer has invested a lot of energy in the field of data v

This article provides three different ways to call Ggplot in Python (IPython Notebook). In the big data age, data visualization is a very hot topic. Every BI vendor invests a lot of energy in the field of data visualization. With its powerful data visualization capabilities

This article provides three different ways to invoke Ggplot in Python (IPython notebook). In the large data age, data visualization is a very hot topic. Every bi manufacturer invests a lot of energy in the field of data visualization. Tableau, with its powerful data visuali

Today's meeting to discuss a half-day of their own research results, colleagues frowned, the first as if she did not understand, the second feeling in front of a bright, but do not know how to landing. Landed this thing, give time, I want to practice my analysis.Today I got a simple, bar chart.is a bar chart that is often played in Excel. Compare the BoxPlot and Ggplot, or ggplot more powerful, and make the

First time, Mark, please.--------------------------------------------------------------------------------------------------------------- ----------------------------------------------Ggplot for people who use R is the artist's hands of the genius, the basic use of the method is not mentioned here, you can directly refer to Http://www.r-bloggers.com/search/ggplotThen sometimes we need to draw a lot of variables, or we need to draw a large number of con

R3.2.2 Version Installation Ggplot2 installed Ggplot2 Today, began to use the R3.2.1 version, but has been an error. The back of a new R3.2.2, but the installation is still the same error, the reason is Munsell this package incompatibility problem,

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 t

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

)) +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

Introduction to Scatter plotsA scatter chart is often used to describe the relationship between two contiguous variables, each of which represents each sample in the target dataset.At the same time, some lines are often fitted in the scatter plot to represent certain models.plot A basic scatter plotThis example uses the following test data set:The drawing method is to first call the Ggplot function to selec

method parameter, which defaults to method= "loess"-smoothing local regression. Parameter span controls how smooth the curve is, and the larger the value the more smoothly the curve. > Qplot (Carat,price,data=sample,geom=c ("point", "smooth"), span=.3) Use Qplot () to draw a more beautiful histogram of the variable carat: > Qplot (carat,data=diamonds,geom= "Histogram", Binwidth=.1,xl

grouping. The production process of frequency distribution table is described in detail in the article "R actual combat nineth: List and Frequency table", no longer repeat. Library (GRID) library (VCD) labels"","30-40","40-50","50-60","60-70",">=") Breaks1, -, +, -, -, -, -) MyTableTRUE) DF as. data.frame (Table (age=mytable)) DFprop.table (Freq)) DFcumsum (freqrate)) DF -,2), cumfreqrate= round (cumfreqrate* -,2)) (2) Plotting frequency distribution histogram To draw a histogram of frequency d

2Read.table ()READ.XLSX ()Install.packages (xlsx)Library (XLSX)If the library () is unsuccessful, refer to: https://wenku.baidu.com/view/1bc6610ece2f0066f433229f.htmlDownload java:https://www.java.com/en/download/manual.jsp> Head (mtcars)MPG cyl DISP hp Drat wt Qsec VS AM gear CarbMazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1Hornet Sport

([ -1.12817385, 1.07053437, -65.81425599, -4.564575 , 6.17156198]), array([ 2.62704721e-01, 2.87680340e-01, 4.15643528e-70, 1.83764399e-05, 2.82461897e-08])) The first array is the t statistic, and the second array is the corresponding P value. Visualization Python has many visualization modules, and the most popular one is the matpalotlib library. We can also select the bokeh and seaborn modules. In my previous blog post, I have explained the function of the box map module in the matplotlib l

). 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

(), and Dcast (), but they can "knead" the data into various shapes. Melt itself means dissolution, decomposition, and its role in a data set is actually split data, its object can be an array, a data frame or a list. > Library (RESHAPE2) > Data (airquality) > str (airquali