data analysis (summary & next step)

      From Mar 25 to May 7, from March 25 to May 7, it took a month and a half to calculate, and I finally completed the preliminary study of this book, from numpy to pandas to matplotlib, I have a preliminary understanding of python and Understand, then the next step is to strengthen and consolidate what you have learned through examples , and spend another week to go over all the basics, summarize and write blogs. 

    

     After this step is completed, start kaggle, find two examples, and read them intensively. [May 07, 2018 22:47:44]

 

File handling : csv, table, json, txt, db
Data sorting : value_counts, argsort, sort_values, searchsorted
Group classification : groupby, pivot_table, stack, unstack, unique, cut, qcut
Data interception : take, loc, iloc, head, tail
Plotting: histograms, graphs (matplotlib, seaborn)
Data merging: merge, concat, cumsum
Data filtering: fillna, list iterative filtering, isin, drop_duplicates
Data transformation: rename, map transformation, apply 

                             So much for the time being, I will classify it after seeing it [2018年05月07日23:08:34]

Continually updated...

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