pandas 用于多个分隔符的熊猫 read_csv()
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pandas read_csv() for multiple delimiters
提问by user77005
I have a file which has data as follows
我有一个文件，其中包含如下数据
1000000 183:0.6673;2:0.3535;359:0.304;363:0.1835
1000001 92:1.0
1000002 112:1.0
1000003 154435:0.746;30:0.3902;220:0.2803;238:0.2781;232:0.2717
1000004 118:1.0
1000005 157:0.484;25:0.4383;198:0.3033
1000006 277:0.7815;1980:0.4825;146:0.175
1000007 4069:0.6678;2557:0.6104;137:0.4261
1000009 2:1.0
I want to read the file to a pandas dataframe seperated by the multiple delimeters \t, :, ;
我想将文件读取到由多个分隔符分隔的 Pandas 数据帧 \t, :, ;
I tried
我试过
df_user_key_word_org = pd.read_csv(filepath+"user_key_word.txt", sep='\t|:|;', header=None, engine='python')
df_user_key_word_org = pd.read_csv(filepath+"user_key_word.txt", sep='\t|:|;', header=None, engine='python')
It gives me the following error.
它给了我以下错误。
pandas.errors.ParserError: Error could be due to quotes being ignored when a multi-char delimiter is used.
pandas.errors.ParserError: Error could be due to quotes being ignored when a multi-char delimiter is used.
Why am I getting this error?
为什么我收到这个错误？
So I thought I'll try to use the regex string. But I am not sure how to write a split regex. r'\t|:|;' doesn't work.
所以我想我会尝试使用正则表达式字符串。但我不确定如何编写拆分正则表达式。r'\t|:|;' 不起作用。
What is the best way to read a file to a pandas data frame with multiple delimiters?
将文件读取到具有多个分隔符的 Pandas 数据框的最佳方法是什么？
采纳答案by Tai
From this question, Handling Variable Number of Columns with Pandas - Python, one workaround to pandas.errors.ParserError: Expected 29 fields in line 11, saw 45.is let read_csvknow about how many rows in advance.
从这个问题，用 Pandas 处理可变数量的列 - Python，一种解决方法 pandas.errors.ParserError: Expected 29 fields in line 11, saw 45.是read_csv提前知道多少行。
my_cols = [str(i) for i in range(45)] # create some row names
df_user_key_word_org = pd.read_csv(filepath+"user_key_word.txt",
sep="\s+|;|:",
names=my_cols,
header=None,
engine="python")
# I tested with s = StringIO(text_from_OP) on my computer
Hope this works.
希望这有效。
