如何在句子的 pandas 列中使用自动更正 [英] How to use autocorrect in Pandas column of sentences

问题描述

我有一列句子，我像这样拆分

I have a column of sentences, which i am splitting like so

df['ColTest'] = df['ColTest'].str.lower().str.split()

我想做的是遍历每个句子中的每个单词并应用autocorrect.spell()

What i am trying to do is loop through each word in each sentence and apply the autocorrect.spell()

for i in df['ColTest']:
for j in i:
    df['ColTest'][i][j].replace(at.spell(j))

这引发了错误

AttributeError:浮动"对象没有属性替换"

AttributeError: 'float' object has no attribute 'replace'

自动拼写自动拼写

DataFrame看起来像

DataFrame looks like

ColTest
This is some test string
that might contain a finger
but this string might contain a toe
and this hass a spel error

我的栏中没有数字...有什么想法吗?

There are no numbers in my column...any ideas please?

推荐答案

使用自动更正库，您需要遍历数据框的行，然后遍历给定行中的单词以应用spell方法.这是一个工作示例:

Using the autocorrect library, you need to iterate through the rows of the dataframe then iterate through the words within a given row to apply the spell method. Here's a working example:

from autocorrect import spell 
import pandas as pd 

df = pd.DataFrame(["and this hass a spel error"], columns=["colTest"])
df.colTest.apply(lambda x: " ".join([spell(i) for i in x.split()]))

此外，如@jpp在下面的注释中所建议的，我们可以避免如下使用lambda:

Also as suggested by @jpp in the comment below, we can avoid using lambdaas follows:

df["colTest"] = [' '.join([spell(i) for i in x.split()]) for x in df['colTest']]

---

输入内容如下:

---

Here's how the input looks like:

                      colTest
0  and this hass a spel error

---

输出:

---

Output:

0    and this has a spell error
Name: colTest, dtype: object

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