使用正则表达式从字符串列中删除小数和非数字

Question

I have a dataframe column with strings like this:

df.column1:
0 R$ 27.467.522,00 (Vinte e sete milhões, quatro...
1 NaN
2 R$ 35.314.312,12 (Trinta e cinco milhões, trezentos...
3 R$ 1.231,34 (Mil duzentos e trinta e um reais e...

I want only to get the numbers, disconsidering the decimals, so it gets to look like this:

df.column1:
0 27467522
1 NaN
2 35314312
3 1231

I'm trying to do that with regex:

df['column1']=df['column1'].str.extract('[REGEX CODE]')

However I'm not used with Regex. I tried solutions like:

df['column1']=df['column1'].str.extract('(.*?,)').str.extract('(\d+)')
df['column1']=df['column1'].str.extract('(\s*,.*)').str.extract('(\d+)')

But I haven't been able to make it right. Can someone help?

Answer 1

Use str.replace then str.extract

df.column1.str.replace('.', '').str.extract(r'(\d+)')

          0
0  27467522
1       NaN
2  35314312
3      1231

Decimals are indicated by commas here, so by replacing periods and using extract to find the first match, the number will be matched, ignoring the decimal.