pd.to_numeric pd.to_msgpack pd.to_pickle 二. apply函数和lambda函数 apply pandas里面如果才有for来遍历循环的话,速度会狠狠狠慢的。使用apply函数来替代执行,速度则会非常快。 apply(func,axis='major',*args,**kwargs) 参数解释: --->func : function函数 --->axis : 作用的轴 --->*args:argument...
与read_csv完全相同。其实read_csv是read_table中分隔符为逗号的一个特例。 示例数据内容如下: importpandasaspd table_data = pd.read_table('table_data.txt', sep=';', names=['col1','col2','col3','col4','col5'])print(table_data) 数据分割常分为两种:一种基于固定宽度,一种基于分割符号。...
读取csv⽂件:pd.read_csv(),写⼊csv⽂件:pd.to_csv() pandas还可以读取⼀下⽂件: read_csv, read_excel, read_hdf, read_sql, read_json, read_msgpack (experimental), read_html, read_gbq (experimental), read_stata, read_sas, read_clipboard, read_pickle; 相应的写⼊: to_csv, to...
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I think u would be better off IMHO using HDFStore or msgpack. (available in 0.13) proper serialization to a binary format is hard when done in a portable reproducible way cpcloudself-assigned thisFeb 17, 2014 wesmunassignedcpcloudOct 12, 2016 ...
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