如何将正则表达式匹配函数的结果放入熊猫数据框中？答案

【问题标题】：How to put the result of a regex match function into pandas dataframe?如何将正则表达式匹配函数的结果放入熊猫数据框中？
【发布时间】：2020-05-05 10:07:40
【问题描述】：

我有这个功能：

def find_regex(regex, text, opzione2= None, opzione3 = None):
    lista = []
    for x in text:
        matches_prima = re.findall(regex, x)
        matches_prima2 = []
        matches_prima3 = []
        if opzione2 is not None:
            matches_prima2 = re.findall(opzione2, x)
            if opzione3 is not None:
                matches_prima3 = re.findall(opzione3, x)
        lunghezza = len(matches_prima) + len(matches_prima2) + len(matches_prima3)
        lista.append(lunghezza)

    print(sum(lista))

假设我的文本是“我爱猫”，正则表达式是“猫”，结果将是一个。

我有

def pandas():
  regex1 = re.compile(r"cat")
  text1 = "I love cats"
  find_regex(regex1, text1) #it returns 1
  df = pd.DataFrame([find_regex(regex1, text1)])
  print(df)

这行不通。正确的做法是什么？

【问题讨论】：

你的find_regex函数中的return语句在哪里？
我没有，是这个问题吗？
如果您仍需要帮助，请考虑执行以下操作：1) 提供您的意见。一个字符串？一份文件？他们看起来怎么样？要搜索的单词列表？它们应该是完整的单词吗？等 2）您需要什么确切的预期输出。否则，我们帮不了你。

标签： python python-3.x regex pandas dataframe

【解决方案1】：

我在这里推断了很多的事情，但我认为至少它让你带有操作代码的增强状态。

用作输入的文本：

Text
Be cxt careful with that cxt.
Be cat careful with that cat.
Stop waiting for the cat to just happen.
He found the cat covered with cats.
The dogmatic people who cat insist are so cathartic!
There should have been a cat and a dog.
Three people with six decades of cat experience.

import pandas as pd
import re

def find_regex(regex, text, opzione2=None, opzione3=None):
    matches_prima = re.findall(regex, text)
    lunghezza = len(matches_prima)
    if opzione2:
        matches_prima2 = re.findall(opzione2, text)
        lunghezza += len(matches_prima2)
        if opzione3:
            matches_prima3 = re.findall(opzione3, text)
            lunghezza += len(matches_prima3)
    return lunghezza

df = pd.read_csv("data.txt")
print(df)

regex1 = r"cat"
regex2 = r"dog"
regex3 = r"people"

df["CntRegex[1]"] = df["Text"].map(lambda x: find_regex(regex1, x))
df["CntRegex[1&2]"] = df["Text"].map(lambda x: find_regex(regex1, x, regex2))
df["CntRegex[1&2&3]"] = df["Text"].map(lambda x: find_regex(regex1, x, regex2, regex3))

with pd.option_context('display.max_colwidth', 25, "display.max_columns", None):
    print(df)

                       Text  CntRegex[1]  CntRegex[1&2]  CntRegex[1&2&3]
0  Be cxt careful with t...            0              0                0
1  Be cat careful with t...            2              2                2
2  Stop waiting for the ...            1              1                1
3  He found the cat cove...            2              2                2
4  The dogmatic people w...            2              3                4
5  There should have bee...            1              2                2
6  Three people with six...            1              1                2

【讨论】：