我有一个数据帧如下,我只需要在一组值的字符串中找到第一个出现。
我无法使用"查找"功能以及正则表达式和字典。如果我使用"findall"功能,它当然是找到所有事件,这不是我需要的。
Text
51000/1-PLASTIC 150 Prange
51034/2-RUBBER KL 100 AA
51556/3-PAPER BD+CM 1 BOXT2
52345/1-FLOW IJ 10place 500 plastic
54975/1-DIVIDER PQR 100 BC
54975/1-SCALE DEF 555 AB Apple
54975/1-PLASTIC ABC 4.6 BB plastic
法典:
import re
L = ['PLASTIC','RUBBER','PAPER','FLOW']
pat = '|'.join(r"b{}b".format(x) for x in L)
df['Result'] = df['Text'].str.find(pat, flags=re.I).str.join(' ')
print(df)
df = df.replace(r'^s*$', np.nan, regex=True)
df = df.replace(np.nan, "Not known", regex=True)
#df['Result'] = df['Result'].str.lower()
预期成果:
Text Result
51000/1-PLASTIC 150 Prange Plastic
51034/2-RUBBER KL 100 AA Rubber
51556/3-PAPER BD+CM 1 BOXT2 Paper
52345/1-FLOW IJ 10place 500 plastic Flow
54975/1-DIVIDER PQR 100 BC Not known
54975/1-SCALE DEF 555 AB Apple Not KNown
54975/1-PLASTIC ABC 4.6 BB plastic Plastic
错误:
TypeError: find(( 得到一个意外的关键字参数 'flags'
使用Series.str.findall
代替find
选择通过索引返回的findall
列表的第一个值str[0]
:
import re
L = ['PLASTIC','RUBBER','PAPER','FLOW']
pat = '|'.join(r"b{}b".format(x) for x in L)
df['Result'] = df['Text'].str.findall(pat, flags=re.I).str[0]
或使用Series.str.extract
:
df['Result'] = df['Text'].str.extract('(' + pat + ')', flags=re.I)
然后将缺失值转换为Not known
:
df['Result'] = df['Result'].fillna("Not known")
最后如有必要,请使用Series.str.capitalize
:
df['Result'] = df['Result'].str.capitalize()
print (df)
Text Result
0 51000/1-PLASTIC 150 Prange Plastic
1 51034/2-RUBBER KL 100 AA Rubber
2 51556/3-PAPER BD+CM 1 BOXT2 Paper
3 52345/1-FLOW IJ 10place 500 plastic Flow
4 54975/1-DIVIDER PQR 100 BC Not known
5 54975/1-SCALE DEF 555 AB Apple Not known
6 54975/1-PLASTIC ABC 4.6 BB plastic Plastic