Question

所以我有一个.csv文件，其中每一行都是这样的：

,11:00:14,4,5.,93.7,0.01,0.0,7,20,0.001,10,49.3,0.01, ,11:00:15,4,5.,94.7,0.04,0.5,7,20,0.005,10,49.5,0.04,

它应该是这样的：

11:00:14,4,5.,93.7,0.01,0.0,7,20,0.001,10,49.3,0.01 11:00:15,4,5.,94.7,0.04,0.5,7,20,0.005,10,49.5,0.04

我认为这就是为什么pandas没有正确创建数据框架的原因。我该怎么做才能删除这些逗号？

生成原始csv文件的代码是

def tsv2csv():

# read tab-delimited file
with open(file_location + tsv_file,'r') as fin:
    cr = csv.reader(fin, delimiter='\t')
    filecontents = [line for line in cr]

# write comma-delimited file (comma is the default delimiter)
# give the exact location of the file
#"newline=''" at the end of the line stops there being spaces between each row
with open(new_csv_file,'w', newline='') as fou:
    cw = csv.writer(fou, quotechar='', quoting=csv.QUOTE_NONE)
    cw.writerows(filecontents)

Answer 1

您可以使用usecols指定要导入的列，如下所示：

import pandas as pd

csv_df = pd.read_csv('temp.csv', header=None, usecols=range(1,13))

这将跳过第一个和最后一个空列。

Answer 2

尾随逗号对应于缺少的数据。在您的数据框中加载时，它们会以NaN形式加载，因此您只需要使用dropna或将它们切片 - 即可将其删除 -

df = pd.read_csv('file.csv', header=None).dropna(how='all', axis=1)

或者，

df = pd.read_csv('file.csv', header=None).iloc[:, 1:-1]

df

         1   2    3     4     5    6   7   8      9   10    11    12
0  11:00:14   4  5.0  93.7  0.01  0.0   7  20  0.001  10  49.3  0.01
1  11:00:15   4  5.0  94.7  0.04  0.5   7  20  0.005  10  49.5  0.04

Answer 3

您可以使用strip删除文本开头和结尾处的任何字符，并提供一个字符串，其中包含您不想作为参数转义的字符。

x = ',11:00:14,4,5.,93.7,0.01,0.0,7,20,0.001,10,49.3,0.01,'
print x.strip(',')
>11:00:14,4,5.,93.7,0.01,0.0,7,20,0.001,10,49.3,0.01

Answer 4

不确定如果它适用于您的情况，您尝试导入了一下：

    df = pd.read_csv('filename', sep=';')

csv行开头和结尾的额外逗号，如何删除？

4 个答案: