熊猫:CSV标头和数据行大小不匹配

时间:2018-10-10 11:33:55

标签: python pandas csv

是否可以指示Pandas忽略超过标题大小的列?

import pandas

with open('test.csv', mode='w') as csv_file:
    csv_file.write("datetime,A\n")
    csv_file.write("2018-10-09 18:00:07, 123\n")

df = pandas.read_csv('test.csv')
print(df)

给出答案:

              datetime    A
0  2018-10-09 18:00:07  123

不过,加载的CSV文件包含更多在标题中定义的数据列:

with open('test.csv', mode='w') as csv_file:
    csv_file.write("datetime,A\n")
    csv_file.write("2018-10-09 18:00:07, 123, ABC, XYZ\n")

df = pandas.read_csv('test.csv')
print(df)

返回:

                        datetime     A
2018-10-09 18:00:07 123      ABC   XYZ

Pandas将标题移到数据的最右边。

我需要不同的行为。我希望熊猫忽略标题以外的数据行。

注意:我无法枚举列,因为这是一个通用的用例。由于某些与我的代码无关的原因,有时会有更多预期的数据。我想忽略多余的数据。

3 个答案:

答案 0 :(得分:2)

似乎Pandas意识到与实际的标头相比,列太多了,并假设前两个(数据)列是(多)索引。

使用usecols中的read_csv参数指定要读取的数据列:

import pandas

with open('test.csv', mode='w') as csv_file:
    csv_file.write("datetime,A\n")
    csv_file.write("2018-10-09 18:00:07, 123, ABC, XYZ\n")

df = pandas.read_csv('test.csv', usecols=[0,1]) 
print(df)

收益

              datetime    A
0  2018-10-09 18:00:07  123

答案 1 :(得分:0)

现在代码显示了问题的答案。

with open('test.csv', mode='w') as csv_file:
    csv_file.write("datetime,A\n")
    csv_file.write("2018-10-09 18:00:07, 123, ABC, XYZ\n")

with open("test.csv") as csv_file:
    for i, line in enumerate(csv_file):
        if i == 0:
            headerCount = line.count(",") + 1
            colCount = headerCount
        elif i == 1:
            dataCount = line.count(",") + 1  
        elif i > 1:
            break
if (headerCount < dataCount):
    print("Warning: Header and data size mismatch. Columns beyond header size will be removed.")
    colCount=headerCount

df = pandas.read_csv('test.csv', usecols=range(colCount))
print(df)

产生:

Warning: Header and data size mismatch. Columns beyond header size will be removed.
              datetime    A
0  2018-10-09 18:00:07  123

答案 2 :(得分:-1)

要使问题更完整,请使用以下技巧:

with open('test.csv', mode='w') as csv_file:
    csv_file.write("datetime,A, B, C\n")
    csv_file.write("2018-10-09 18:00:07, 123\n")

with open("test.csv") as csv_file:
    for i, line in enumerate(csv_file):
        if i == 0:
            headerCount = line.count(",") + 2
        elif i == 1:
            dataCount = line.count(",") + 2  
            if (headerCount != dataCount):
                print("Warning: Header and data size mismatch. Columns beyond header size will be removed.")
        elif i > 1:
            break


df = pandas.read_csv('test.csv', usecols=range(dataCount-1))
print(df)

给出正确的熊猫对象。

Warning: Header and data size mismatch. Columns beyond header size will be removed.
              datetime    A
0  2018-10-09 18:00:07  123
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