我已获得以下CSV文件,可将其导入Pandas DataFrame
,,,,Facet,Facet,Facet,Facet,Value,Value,Value,Value
Snipit,,,,0,0,0,0,0,0,0,0
Grainy,,,,0,0,1,2,0,0,1,2
Arroyo,Position,Chunk,Grade,,,,,,,,
0,0,0,5,2.0,2.0,2.0,0.0,2.0,2.0,2.0,1.2
0,0,0,21,0.0,0.0,0.0,2.0,1.0,1.0,1.0,2.0
该表由Arroyo,Position,Chunk,Grade和columns进行了多索引 没有,“ Snipit”,“ Grainy”,“ Tiny”已保存到CSV文件。
当尝试使用pd.read_csv时,我得到以下信息:
Unnamed: 0 Unnamed: 1 Unnamed: 2 Unnamed: 3 Facet Facet.1 Facet.2 Facet.3 Value Value.1 Value.2 Value.3
0 Snipit NaN NaN NaN 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1 Grainy NaN NaN NaN 0.0 0.0 1.0 2.0 0.0 0.0 1.0 2.0
2 Tiny NaN NaN NaN 0.0 1.0 0.0 2.0 0.0 1.0 0.0 2.0
3 Arroyo Position Chunk Grade NaN NaN NaN NaN NaN NaN NaN NaN
4 0 0 0 5 2.0 2.0 2.0 0.0 2.0 2.0 2.0 1.2
5 0 0 0 21 0.0 0.0 0.0 2.0 1.0 1.0 1.0 2.0
所需的输出
Facet Facet Facet Facet Value Value Value Value
Snipit 0 0 0 0 0 0 0 0
Grainy 0 0 1 2 0 0 1 2
Tiny 0 1 0 2 0 1 0 2
Arroyo Position Chunk Grade
0 0 0 5 2.0 2.0 2.0 0.0 2.0 2.0 2.0 1.2
0 0 0 21 0.0 0.0 0.0 2.0 1.0 1.0 1.0 2.0
我知道我需要定义索引和列,但是只有我可以找到使用平面文件的地方了。就我而言,我正在处理已处理的数据,找不到该示例。
我可以将这样的文件导入pandas DataFrame中吗?从阅读的内容中我什么都看不到
谢谢。
答案 0 :(得分:0)
您可以在index_col
中使用read_csv()
参数设置多索引:
df = pd.read_csv('data.csv', index_col=[0,1,2,3])