Python (which is said to be) is increasing its existence in the world of data science as a data analysis language. Here's a summary of data analysis in Python, especially how to use Pandas.
・ I think it is especially useful for R users who want to use Python. ・ The focus is on basic data handling methods.
【Slide Share】Python for R uses How to reproduce the notation used in R in Python A quick reference table is listed, and I tried to do what I was doing in R with Python I think it's quite useful. http://www.slideshare.net/ajayohri/python-for-r-users
【Pandas Official】Pandas -comparison with R Similar to the above, when I wanted to realize the grammar in R with Pandas Notation comparison is written earnestly. http://pandas.pydata.org/pandas-docs/stable/comparison_with_r.html
◆Comparing dplyr in R and Pandas God page comparing the correspondence between the notation in Dplyr and the notation in Pandas You can do it with R, but it's refreshing because it says that you can't do features that Pandas doesn't have. Since it is an explanation using the standard Flight data in Dplyr, R user should be familiar with it. http://goo.gl/7dNzE6
◆Numpy for R users RNumpy grammar in R (ry) There is quite a volume and it seems to be usable. http://mathesaurus.sourceforge.net/r-numpy.html
【Pandas Official】Ten Minutes Work to Pandas http://pandas.pydata.org/pandas-docs/stable/10min.html
The notation for accessing pd.DF is detailed. ix [], iloc [], etc. http://sinhrks.hatenablog.com/entry/2014/11/12/233216
Basics of how to handle DF and Series http://goo.gl/FoqmCs
Take a look at this article too After reading the above variously, I will summarize the methods often used in Pandas
◆ Elementary summary method list of data manipulation in Python Pandas http://qiita.com/hik0107/items/d991cc44c2d1778bb82e