从python中的字符串集中删除不需要的字符
我正在尝试清理一组字符串以删除不需要的字符 输入 想要的产出从python中的字符串集中删除不需要的字符,python,string,re,Python,String,Re,我正在尝试清理一组字符串以删除不需要的字符 输入 想要的产出 Lethal Lunch Muscika Typhoon Ten Wentworth Falls One Night Stand Dancinginthewoods Case Key 我试过这个 re.findall('([a-zA-Z ]*)\d*.*',final_df.loc[index, 'Horse']) 这将删除数字后的所有内容,但在第一个条目上保留t。我想知道是否有更好的方法?我会使用re.split: for d
Lethal Lunch
Muscika
Typhoon Ten
Wentworth Falls
One Night Stand
Dancinginthewoods
Case Key
我试过这个
re.findall('([a-zA-Z ]*)\d*.*',final_df.loc[index, 'Horse'])
这将删除数字后的所有内容,但在第一个条目上保留t。我想知道是否有更好的方法?我会使用
re.split
:
for d in data.splitlines():
print(re.split(r'\s+t?[0-9]\+?', d)[0])
结果
说明:它在指定模式匹配的位置拆分字符串,然后获取第一部分。您可能想要调整它,以便其他模式也匹配
熊猫
我刚刚注意到你似乎在使用熊猫——假设你的df看起来是这样的:
Horse
0 Lethal Lunch t5+ 0 0 D 10 t5+ Michael Bell . A...
1 Muscika 1 v5+ W5+ 0 0 D 5 v5+ W5+ D O'Meara . ...
2 Typhoon Ten 1 0 0 D 13 R Hannon . Luke Catton7 .
3 Wentworth Falls 1 cp5+ 0 0 C D 45 cp5+ G Harke...
4 One Night Stand 0 0 D 34 W Jarvis . Silvestre ...
5 Dancinginthewoods 1 0 0 D 24 D Ivory . 14 Jami...
6 Case Key 1 v3 0 0 D 13 v3 M Appleby . Andrew M...
你能行
from operator import itemgetter
df["name"] = df.Horse.str.split('\s+t?[0-9]\+?').map(itemgetter(0))
要获得此信息:
Horse name
0 Lethal Lunch t5+ 0 0 D 10 t5+ Michael Bell . A... Lethal Lunch
1 Muscika 1 v5+ W5+ 0 0 D 5 v5+ W5+ D O'Meara . ... Muscika
2 Typhoon Ten 1 0 0 D 13 R Hannon . Luke Catton7 . Typhoon Ten
3 Wentworth Falls 1 cp5+ 0 0 C D 45 cp5+ G Harke... Wentworth Falls
4 One Night Stand 0 0 D 34 W Jarvis . Silvestre ... One Night Stand
5 Dancinginthewoods 1 0 0 D 24 D Ivory . 14 Jami... Dancinginthewoods
6 Case Key 1 v3 0 0 D 13 v3 M Appleby . Andrew M... Case Key
像这样的方法应该会奏效:
filtered_text = list()
for line in text:
part = ""
for word in text.split(" "):
if len(word) <= 3:
break
else:
part = str(part) + " " + str(word)
part = part[1:] # skip first space
filtered_text.append(part)
filtered_text=list()
对于文本中的行:
part=“”
对于文本中的单词。拆分(“”):
如果len(word)像这样的东西就足够了吗
input = [
"Lethal Lunch t5+ 0 0 D 10 t5+ Michael Bell . Alex Jary7 .",
"Muscika 1 v5+ W5+ 0 0 D 5 v5+ W5+ D O'Meara . Cam Hardie . C5",
"Typhoon Ten 1 0 0 D 13 R Hannon . Luke Catton7 .",
"Wentworth Falls 1 cp5+ 0 0 C D 45 cp5+ G Harker . Connor Beasley .",
"One Night Stand 0 0 D 34 W Jarvis . Silvestre De Sousa . 30 C1 C5",
"Dancinginthewoods 1 0 0 D 24 D Ivory . 14 Jamie Spencer . 30",
"Case Key 1 v3 0 0 D 13 v3 M Appleby . Andrew Mullen . 14",
]
for inp in input:
print(re.findall(r'\b[a-zA-Z ]+\b', inp)[0])
我们基本上忽略了带有数字或奇怪符号的单词。
输出:
Lethal Lunch
Muscika
Typhoon Ten
Wentworth Falls
One Night Stand
Dancinginthewoods
Case Key
太棒了,谢谢你加上熊猫片,真的很有帮助。非常感谢。
input = [
"Lethal Lunch t5+ 0 0 D 10 t5+ Michael Bell . Alex Jary7 .",
"Muscika 1 v5+ W5+ 0 0 D 5 v5+ W5+ D O'Meara . Cam Hardie . C5",
"Typhoon Ten 1 0 0 D 13 R Hannon . Luke Catton7 .",
"Wentworth Falls 1 cp5+ 0 0 C D 45 cp5+ G Harker . Connor Beasley .",
"One Night Stand 0 0 D 34 W Jarvis . Silvestre De Sousa . 30 C1 C5",
"Dancinginthewoods 1 0 0 D 24 D Ivory . 14 Jamie Spencer . 30",
"Case Key 1 v3 0 0 D 13 v3 M Appleby . Andrew Mullen . 14",
]
for inp in input:
print(re.findall(r'\b[a-zA-Z ]+\b', inp)[0])
Lethal Lunch
Muscika
Typhoon Ten
Wentworth Falls
One Night Stand
Dancinginthewoods
Case Key