Question

我尝试使用pandas.read_csv导入csv文件。该文件如下：

    "COL_A","COL_B","COL_C"
    "ROW1COLA","ROW1COLB","ROW1COLC","ROW1COLD"
    "ROW2COLA","ROW2COLB","ROW2COLC","ROW2COLD"
    "ROW3COLA","ROW3COLB","ROW3COLC","ROW3COLD"
    "ROW4COLA","ROW4COLB","ROW4COLC","ROW4COLD"
    "ROW5COLA","ROW5COLB","ROW5COLC","ROW5COLD"
    "ROW6COLA","ROW6COLB","ROW6COLC","ROW6COLD"
    "ROW7COLA","ROW7COLB","ROW7COLC","ROW7COLD"

我第一次尝试跑了：

    data = pd.read_csv('broken.csv')

我得到了：

                 COL_A     COL_B     COL_C
    ROW1COLA  ROW1COLB  ROW1COLC  ROW1COLD
    ROW2COLA  ROW2COLB  ROW2COLC  ROW2COLD
    ROW3COLA  ROW3COLB  ROW3COLC  ROW3COLD
    ROW4COLA  ROW4COLB  ROW4COLC  ROW4COLD
    ROW5COLA  ROW5COLB  ROW5COLC  ROW5COLD
    ROW6COLA  ROW6COLB  ROW6COLC  ROW6COLD
    ROW7COLA  ROW7COLB  ROW7COLC  ROW7COLD

设置index_col = False

    data = pd.read_csv('broken.csv',index_col=False)

我得到了

          COL_A     COL_B     COL_C
    0  ROW1COLA  ROW1COLB  ROW1COLC
    1  ROW2COLA  ROW2COLB  ROW2COLC
    2  ROW3COLA  ROW3COLB  ROW3COLC
    3  ROW4COLA  ROW4COLB  ROW4COLC
    4  ROW5COLA  ROW5COLB  ROW5COLC
    5  ROW6COLA  ROW6COLB  ROW6COLC
    6  ROW7COLA  ROW7COLB  ROW7COLC

如果我添加前缀=＆＃39; X＆＃39;

    data = pd.read_csv('broken.csv',index_col=False,prefix='X')

我得到了

          COL_A     COL_B     COL_C
    0  ROW1COLA  ROW1COLB  ROW1COLC
    1  ROW2COLA  ROW2COLB  ROW2COLC
    2  ROW3COLA  ROW3COLB  ROW3COLC
    3  ROW4COLA  ROW4COLB  ROW4COLC
    4  ROW5COLA  ROW5COLB  ROW5COLC
    5  ROW6COLA  ROW6COLB  ROW6COLC
    6  ROW7COLA  ROW7COLB  ROW7COLC

与read_table相同

    data = pd.read_table('broken.csv',index_col=True,sep=',')

我想知道pandas是否有任何方法可以自动分配标题并获取缺少标题列的值

Answer 1

没有名称/标题的第一列被视为索引列。

您还应该正确使用index_col参数：

data = pd.read_table('broken.csv',index_col=[0],sep=',')

如果您的第一列包含数据而不是索引，则可以跳过第一行，指定列的名称，并指示read_csv您不想读取标题：

cols = ['col1','col2','col3','col4']
data = pd.read_table('broken.csv',sep=',', skiprows=[0], header=None, names=cols)

Answer 2

我认为你可以使用read_csv参数header=0，第一行设置为列，然后被参数names覆盖为自定义列名。省略参数sep=','，因为它默认为：

import pandas as pd
import io

temp=u'''"COL_A","COL_B","COL_C"
"ROW1COLA","ROW1COLB","ROW1COLC","ROW1COLD"
"ROW2COLA","ROW2COLB","ROW2COLC","ROW2COLD"
"ROW3COLA","ROW3COLB","ROW3COLC","ROW3COLD"
"ROW4COLA","ROW4COLB","ROW4COLC","ROW4COLD"
"ROW5COLA","ROW5COLB","ROW5COLC","ROW5COLD"
"ROW6COLA","ROW6COLB","ROW6COLC","ROW6COLD"
"ROW7COLA","ROW7COLB","ROW7COLC","ROW7COLD"'''
#after testing replace io.StringIO(temp) to filename
df = pd.read_csv(io.StringIO(temp), header=0, names=['a','b','c','d'])

print df
          a         b         c         d
0  ROW1COLA  ROW1COLB  ROW1COLC  ROW1COLD
1  ROW2COLA  ROW2COLB  ROW2COLC  ROW2COLD
2  ROW3COLA  ROW3COLB  ROW3COLC  ROW3COLD
3  ROW4COLA  ROW4COLB  ROW4COLC  ROW4COLD
4  ROW5COLA  ROW5COLB  ROW5COLC  ROW5COLD
5  ROW6COLA  ROW6COLB  ROW6COLC  ROW6COLD
6  ROW7COLA  ROW7COLB  ROW7COLC  ROW7COLD

带有参数header=None的更通用的解决方案，对于带有skiprows=[0]标题的列名称没有跳过第一行，但缺少最后一列的名称：

import pandas as pd
import io

temp=u'''"COL_A","COL_B","COL_C"
"ROW1COLA","ROW1COLB","ROW1COLC","ROW1COLD"
"ROW2COLA","ROW2COLB","ROW2COLC","ROW2COLD"
"ROW3COLA","ROW3COLB","ROW3COLC","ROW3COLD"
"ROW4COLA","ROW4COLB","ROW4COLC","ROW4COLD"
"ROW5COLA","ROW5COLB","ROW5COLC","ROW5COLD"
"ROW6COLA","ROW6COLB","ROW6COLC","ROW6COLD"
"ROW7COLA","ROW7COLB","ROW7COLC","ROW7COLD"'''
#after testing replace io.StringIO(temp) to filename
df = pd.read_csv(io.StringIO(temp), header=None, skiprows=[0])

print df
          0         1         2         3
0  ROW1COLA  ROW1COLB  ROW1COLC  ROW1COLD
1  ROW2COLA  ROW2COLB  ROW2COLC  ROW2COLD
2  ROW3COLA  ROW3COLB  ROW3COLC  ROW3COLD
3  ROW4COLA  ROW4COLB  ROW4COLC  ROW4COLD
4  ROW5COLA  ROW5COLB  ROW5COLC  ROW5COLD
5  ROW6COLA  ROW6COLB  ROW6COLC  ROW6COLD
6  ROW7COLA  ROW7COLB  ROW7COLC  ROW7COLD

Pandas read_csv，读取缺少标题元素的csv文件

2 个答案: