列数据中的python pandas read_csv分隔符
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python pandas read_csv delimiter in column data
提问by Thomas Pazur
I'm having this type of CSV file:
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
I want to get this data into da pandas.DataFrame.
But read_csv(sep=";")throws exceptions due to the semicolon in the user generated message column in line 2 (In my opinion: It's cool; or at least not bad). All remaining columns constantly have numeric dtypes.
我想将这些数据放入 da pandas.DataFrame。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 dtypes。
What is the most convenient method to manage this?
管理这个最方便的方法是什么？
回答by DSM
Dealing with unquoted delimiters is always a nuisance. In this case, since it looks like the broken text is known to be surrounded by three correctly-encoded columns, we can recover. TBH, I'd just use the standard Python reader and build a DataFrame once from that:
处理不带引号的分隔符总是一件麻烦事。在这种情况下，由于看起来损坏的文本被三个正确编码的列包围，我们可以恢复。TBH，我只是使用标准的 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)
which produces
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
Then we can immediately save it and get something quoted correctly:
然后我们可以立即保存它并正确引用一些内容：
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
