It is true that data visualization can be considered as the last process of data analysis work, the previous homework done well, if not well presented, that is even if it is a foot in the door, a failure ...... Below to give you a list of good data visualization tools, I hope to be able to bring some of your learning or work help.
1, the powerful R visualization package - ggplot2
R is a biased statistical analysis of the scripting language software, based on the S language development, if you are the R language loyal fans, I believe that you will not be unaware of R in a separate drawing package - ggplot2, the reason why to ggplot2 "Powerful" title, on the one hand, really can easily cope with various areas of the image drawing, static, dynamic, name, personalized special; on the other hand, I am learning statistics, natural relative familiarity with this package.
ggplot2 created by Hadley Wickham in 2005. The reason for its popularity is the idea of breaking down graphs into morphemes (e.g., scales, layers). ggplot2 can be used as an alternative to the basic plotting packages for the R language, and ggplot2 comes preconfigured with a wide range of print and web sizes.
Compared to the R base plotting package, ggplot2 allows the user to add, delete, or transform elements in the diagram at a more abstract level. The price of this abstraction is execution speed. ggplot2 is more time consuming than the lattice plotting package.
2. The da Vinci of data science - matplotlib
If you're a data analyst who prefers to use python, then I'm sure you're more than familiar with matplotlib, the visual interface to the Python language and its mathematical extension, NumPy.
The advantages of Matplotlib: default plotting styles with built-in code; deep integration with Python; more beautiful graphics compared to Gnuplot. On the downside, it is highly dependent on other packages such as Numpy, and only works with Python: it is difficult to use it in languages other than Python.
Let's use matplotlib in python to make a scatterplot to try:
import matplotlib.pyplot as plt
from numpy.random import rand
a = rand(100)
b = rand(100)
plt.scatter(a,b)
plt.show()
3, menu-based operation of the user's gospel-Tableau
Recently, there are companies recruiting requirements will be Tbaleau, I have only recently become aware of this software
Recently, some companies have asked for Tbaleau.
tableua is a software company headquartered in Seattle, Washington, U.S.A. that produces interactive data visualization products with a focus on business intelligence. tableau products query relational databases, OLAP multidimensional datasets, cloud databases, and spreadsheets, and then generates many chart types. The product can also extract data from its in-memory data engine and store and retrieve it.
4, Microsoft loyal users can not be separated from the interactive labeling board - PowerBI
Power BI is a business analysis services provided by Microsoft. It provides interactive visualization with self-service business intelligence features, end-users can create their own reports and dashboards without relying on information technology staff or database administrators.PowerBI and excel seamless access to the professional enhancement version of excel is not required to install PowerBI plug-ins, open the excel can be used.
Of course, some data analysis software with pivot tables, mapping functions, such as MySQL, SPSS, but data visualization is not as the main function, here is not as good as the above more detailed.