基于REGEX结果创建具有0和1值的新列

Question

我的dataframe具有值：

data_df
0         student
1         sample text
2         student
3         no students
4         sample texting
5         random sample

我使用正则表达式用"学生"提取行，我的结果如下：

regexdf
0         student
2         student

我的目标是在主数据框架中创建一个新的列，并具有0和1值。即第0行应该为1，第5行应该为零。（作为" RegexDf"第0和2行中的"学生"）如何匹配两者中的索引并创建列？

Answer 1

使用REGEX：

data_df = data_df.assign(regexdf = data_df[1].str.extract(r'(student)b', expand=False))
data_df['student'] = data_df['regexdf'].notnull().mul(1)
print(data_df)

输出：

                 1  regexdf  student
0         student  student        1
1     sample text      NaN        0
2         student  student        1
3     no students      NaN        0
4  sample texting      NaN        0
5   random sample      NaN        0

编辑

df_out = data_df.join(regexdf, rsuffix='regex')
df_out['pattern'] = df_out['1regex'].notnull().mul(1)
df_out['Count_Pattern'] = df_out['pattern'].cumsum()
print(df_out)

输出：

                1   1regex  pattern  Count_Pattern
0         student  student        1              1
1     sample text      NaN        0              1
2         student  student        1              2
3     no students      NaN        0              2
4  sample texting      NaN        0              2
5   random sample      NaN        0              2

Answer 2

您也可以做

df['bool'] = df[1].eq('student').astype(int)

或

df['bool'] = df[1].str.match(r'(student)b').astype(int)
                1  bool
0         student     1
1     sample text     0
2         student     1
3     no students     0
4  sample texting     0
5   random sample     0

如果您想要一个新的数据框，则

ndf = df[df[1].eq('student')].copy()