如何在Pandas中读取奇怪的csv文件？

Question

我想阅读下面显示的示例csv文件

--------------
 |A|B|C| 
--------------
 |1|2|3| 
--------------
 |4|5|6| 
--------------
 |7|8|9| 
--------------

我试过了

pd.read_csv("sample.csv",sep="|")

但它没有奏效.

我该怎么读这个csv？

Answer 1

您可以添加参数comment来read_csv,然后用删除列NaN的dropna:

import pandas as pd
import io

temp=u"""--------------
|A|B|C|
--------------
|1|2|3|
--------------
|4|5|6|
--------------
|7|8|9|
--------------"""
#after testing replace io.StringIO(temp) to filename
df = pd.read_csv(io.StringIO(temp), sep="|", comment='-').dropna(axis=1, how='all')

print (df)
   A  B  C
0  1  2  3
1  4  5  6
2  7  8  9

更一般的解决方案

import pandas as pd
import io

temp=u"""--------------
|A|B|C|
--------------
|1|2|3|
--------------
|4|5|6|
--------------
|7|8|9|
--------------"""
#after testing replace io.StringIO(temp) to filename
#separator is char which is NOT in csv
df = pd.read_csv(io.StringIO(temp), sep="^", comment='-')

#remove first and last | in data and in column names
df.iloc[:,0] = df.iloc[:,0].str.strip('|') 
df.columns = df.columns.str.strip('|')
#split column names
cols = df.columns.str.split('|')[0]
#split data
df = df.iloc[:,0].str.split('|', expand=True)
df.columns = cols
print (df)
   A  B  C
0  1  2  3
1  4  5  6
2  7  8  9