Python数据分析博文汇总
* Pandas重复值处理函数drop_duplicates()
<https://blog.csdn.net/W_weiying/article/details/80231896>
* Pandas数据库缺失值处理函数dropna
<https://blog.csdn.net/W_weiying/article/details/80232127>
* Pandas中slice函数字段抽取
<https://blog.csdn.net/W_weiying/article/details/80235581>
* python数据分析-DataFrame数据框基本知识
<https://blog.csdn.net/W_weiying/article/details/80241530>
* Pandas数据库数据抽取 <https://blog.csdn.net/W_weiying/article/details/80390194>
* Numpy.random.randint()函数用法及源码
<https://blog.csdn.net/W_weiying/article/details/80390416>
* Pandas.concat()函数用法及源码
<https://blog.csdn.net/W_weiying/article/details/80390463>
* Pandas数据框列合并详解 <https://blog.csdn.net/W_weiying/article/details/80393524>
* Pandas.merge()函数用法及源码
<https://blog.csdn.net/W_weiying/article/details/80394036>
* Pandas之数据框框运算 <https://blog.csdn.net/W_weiying/article/details/80394243>
* Pandas之数据标准化 <https://blog.csdn.net/W_weiying/article/details/80396470>
* Pandas.cut函数用法及源码 <https://blog.csdn.net/W_weiying/article/details/80396638>
* python数据框空格值处理 <https://blog.csdn.net/W_weiying/article/details/80235367>
* Pandas.split()函数用法及源码
<https://blog.csdn.net/W_weiying/article/details/80235961>
字段拆分:是指按照固定的字符,拆分已有字符串
函数用法:split(sep,n,expand=false)
sep表示用于分割的字符;n表格分割成多少列;expand表示是否展开为数据款,True输出Series,False输出Dataframe。
from pandas import Series; from pandas import DataFrame; from pandas import
read_csv; df =
read_csv("E://pythonlearning//datacode//firstpart//4//4.7//data.csv"); newDF =
df['name'].str.split(' ', 2, True); newDF.columns = ['band', 'name','size'];
运行代码前四行得到:
运行代码后两行得到:
源代码:https://download.csdn.net/download/w_weiying/10427108
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