pandas 带双引号的熊猫数据
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pandas data with double quote
提问by Gerrit
I am trying to read a large dataset in .csv format which is update automatically using the pandas library. The problem is that in my data, the first row is a string without double quotation marks, and the other colums are strings with double quotation marks. It is not possible for me to adjust the .csv file manually.
我正在尝试读取 .csv 格式的大型数据集，该数据集使用 Pandas 库自动更新。问题是在我的数据中，第一行是没有双引号的字符串，其他列是有双引号的字符串。我无法手动调整 .csv 文件。
A simplified dataset would look like this
一个简化的数据集看起来像这样
- A,"B","C","D"
- comp_a,"tree","house","door"
- comp_b,"truck","red","blue"
- A B C D”
- comp_a、“树”、“房子”、“门”
- comp_b，“卡车”，“红色”，“蓝色”
I need the data to be stored as separate columns without the quotation marks like this:
我需要将数据存储为不带引号的单独列，如下所示：
- A B C D
- comp_a tree house door
- comp_b truck red blue
- A B C D
- comp_a 树屋门
- comp_b 卡车红色蓝色
I tried using
我尝试使用
import pandas as pd
df_csv = pd.read(path_to_file,delimiter=',')
which gives me the complete header as a single variable for the last column
这给了我完整的标题作为最后一列的单个变量
- A,"B","C","D"
- comp_a "tree" "house" "door"
- comp_b "truck" "red" "blue"
- A B C D”
- comp_a“树”“房子”“门”
- comp_b“卡车”“红色”“蓝色”
The closest result to the one i need was by using the following
最接近我需要的结果是使用以下
df_csv = pd.read(path_to_file,delimiter=',',quoting=3)
which correctly recognizes each column, but adds in a bunch of extra double quotes.
它正确识别每一列，但添加了一堆额外的双引号。
- "A ""B"" ""C"" ""D"""
- "comp_a ""tree"" ""house"" ""door"""
- "comp_b ""truck"" ""red"" ""blue"""
- “A B C D”””
- “comp_a”“树”““房子”““门”“”
- "comp_b""卡车""""红色""""蓝色"""
Setting quoting to a value from 0 to 2 just reads an entire row as a single column.
将引用设置为 0 到 2 之间的值只会将整行作为单列读取。
Does anyone know how I can remove all quotation marks when reading the .csv file?
有谁知道如何在阅读 .csv 文件时删除所有引号？
回答by Federico Gentile
Just load the data with pd.read_csv()and then use .replace('"','', regex=True)
只需加载数据pd.read_csv()然后使用.replace('"','', regex=True)
In one line it would be:
在一行中，它将是：
df = pd.read_csv(filename, sep=',').replace('"','', regex=True)
To set the columns names:
要设置列名称：
df.columns = df.iloc[0]
And drop row 0:
并删除第 0 行：
df = df.drop(index=0).reset_index(drop=True)
回答by Nihal
you can replace "after read_csvand save that file again using df_csv.to_csv('fname')
您可以"在read_csv使用后替换并再次保存该文件df_csv.to_csv('fname')
df_csv.apply(lambda x:x.str.replace('"', ""))
回答by Kay Wittig
Consider your data in a file data.csv like
考虑文件 data.csv 中的数据，例如
$> more data.csv
A,"B","C","D"
comp_a,"tree","house","door"
comp_b,"truck","red","blue"
Perhaps a newer pandas version would solve your problem from itself, e.g. at pd.__version__ = '0.23.1'
也许较新的Pandas版本会自己解决您的问题，例如在 pd.__version__ = '0.23.1'
In [1]: import pandas as pd
In [2]: pd.read_csv('data.csv')
Out[2]:
A B C D
0 comp_a tree house door
1 comp_b truck red blue
Otherwise apply a replace on the read-out
否则在读数上应用替换
pd.read_csv('data.csv').replace('"', '')
