我有这种类型的 CSV 文件:
12012;My Name is Mike. What is your's?;3;0
1522;In my opinion: It's cool; or at least not bad;4;0
21427;Hello. I like this feature!;5;1
我想将此数据放入 da pandas.DataFrame
中。
但是 read_csv(sep=";")
由于第 2 行中用户生成的消息列中的分号而引发异常(在我看来:这很酷;或者至少还不错)。所有剩余的列始终具有数字数据类型。
管理这个最方便的方法是什么?
最佳答案
处理不带引号的定界符总是一件麻烦事。在这种情况下,由于已知损坏的文本被三个正确编码的列包围,我们可以恢复。 TBH,我只使用标准的 Python 阅读器并从中构建一个 DataFrame:
import csv
import pandas as pd
with open("semi.dat", "r", newline="") as fp:
reader = csv.reader(fp, delimiter=";")
rows = [x[:1] + [';'.join(x[1:-2])] + x[-2:] for x in reader]
df = pd.DataFrame(rows)
产生
0 1 2 3
0 12012 My Name is Mike. What is your's? 3 0
1 1522 In my opinion: It's cool; or at least not bad 4 0
2 21427 Hello. I like this feature! 5 1
然后我们可以立即保存它并得到正确引用的内容:
In [67]: df.to_csv("fixedsemi.dat", sep=";", header=None, index=False)
In [68]: more fixedsemi.dat
12012;My Name is Mike. What is your's?;3;0
1522;"In my opinion: It's cool; or at least not bad";4;0
21427;Hello. I like this feature!;5;1
In [69]: df2 = pd.read_csv("fixedsemi.dat", sep=";", header=None)
In [70]: df2
Out[70]:
0 1 2 3
0 12012 My Name is Mike. What is your's? 3 0
1 1522 In my opinion: It's cool; or at least not bad 4 0
2 21427 Hello. I like this feature! 5 1
关于列数据中的python pandas read_csv定界符,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/30898935/