pandas 如何使用 Python 从数据框中的每个字符串中获取第一个单词？
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How can I get the first word from each string in my Dataframe using Python?
提问by twhale
I have a Pandas DataFrame called "data" with 2 columns and 50 rows filled with one or two lines of text each, imported from a .tsv file. Some of the questions may contain integers and floats, besides strings. I am trying to extract the first word of every sentence (in both columns), but consistently get this error: AttributeError: 'DataFrame' object has no attribute 'str'.
我有一个名为“data”的 Pandas DataFrame，有 2 列和 50 行，每行填充一两行文本，从 .tsv 文件导入。除了字符串之外，一些问题可能包含整数和浮点数。我试图提取每个句子的第一个单词（在两列中），但始终收到此错误：AttributeError: 'DataFrame' object has no attribute 'str'。
At first, I thought the error was due to my wrong use of "data.str.split", but all changes I could Google failed. Then I through the file might not be composed of all strings. So I tried "data.astype(str)" on the file, but the same error remained. Any suggestions? Thanks a lot!
起初，我认为错误是由于我错误地使用了“data.str.split”，但我能谷歌的所有更改都失败了。然后我通过的文件可能不是所有的字符串组成。所以我在文件上尝试了“data.astype(str)”，但同样的错误仍然存在。有什么建议？非常感谢！
Here is my code:
这是我的代码：
import pandas as pd
questions = "questions.tsv"
data = pd.read_csv(questions, usecols = [3], nrows = 50, header=1, sep="\t")
data = data.astype(str)
first_words = data.str.split(None, 1)[0]
采纳答案by jezrael
Use:
用：
first_words = data.apply(lambda x: x.str.split().str[0])
Or:
或者：
first_words = data.applymap(lambda x: x.split()[0])
Sample:
样本：
data = pd.DataFrame({'a':['aa ss ss','ee rre', 1, 'r'],
'b':[4,'rrt ee', 'ee www ee', 6]})
print (data)
a b
0 aa ss ss 4
1 ee rre rrt ee
2 1 ee www ee
3 r 6
data = data.astype(str)
first_words = data.apply(lambda x: x.str.split().str[0])
print (first_words)
a b
0 aa 4
1 ee rrt
2 1 ee
3 r 6
first_words = data.applymap(lambda x: x.split()[0])
print (first_words)
a b
0 aa 4
1 ee rrt
2 1 ee
3 r 6
回答by piRSquared
The problem is that you attempted to use the pd.Series.strstring accessor on a pd.DataFrame. Unfortunately, it is a pd.Seriesonly attribute. That means you need to use it in a pd.Seriescontext. You can accomplish in several ways.
问题是您试图pd.Series.str在pd.DataFrame. 不幸的是，它是pd.Series唯一的属性。这意味着您需要在pd.Series上下文中使用它。您可以通过多种方式完成。
Setup
Assume your dataframe looked like this
设置
假设您的数据框看起来像这样
Col1 Col2
0 this is a test hello world
1 this is another pandas123
2 test3 tommy trojan
3 etcetera one more sentence
Option 1
Use stackto convert a 2-dimensional dataframe into a series... then use the string accessor
选项1
使用stack的2维数据帧转换成一系列的...然后用串访问
# Make a
# Series
# /----\
df.stack().str.split(n=1).str[0].unstack()
# \_____/
# Turn it
# Back
Col1 Col2
0 this hello
1 this pandas123
2 test3 tommy
3 etcetera one
Option 2
Or you can use pd.DataFrame.applyto use the pd.Series.straccessor on each column separately.
This is covered in @jezrael's answer.
选项 2
或者您可以单独pd.DataFrame.apply使用pd.Series.str每列上的访问器。
这在@jezrael 的回答中有所涉及。
df.apply(lambda x: x.str.split(n=1).str[0])
Col1 Col2
0 this hello
1 this pandas123
2 test3 tommy
3 etcetera one
Option 3
Use a comprehension
选项 3
使用理解
pd.DataFrame({c: df[c].str.split(n=1).str[0] for c in df})
Col1 Col2
0 this hello
1 this pandas123
2 test3 tommy
3 etcetera one
You'll notice that in all options, we used the stron a pd.Seriesobject and not a pd.DataFrameobject.
您会注意到，在所有选项中，我们都使用str了pd.Series对象而不是pd.DataFrame对象。
