问题描述
这是我的数据框中 pyspark 列(字符串)的一个小示例.
This is a small example of a pyspark column (String) in my dataframe.
column | new_column
------------------------------------------------------------------------------------------------- |--------------------------------------------------
Hoy es día de ABC/KE98789T983456 clase. | 98789
------------------------------------------------------------------------------------------------- |--------------------------------------------------
Como ABC/KE 34562Z845673 todas las mañanas | 34562
------------------------------------------------------------------------------------------------- |--------------------------------------------------
Hoy tiene ABC/KE 110330/L63868 clase de matemáticas, | 110330
------------------------------------------------------------------------------------------------- |--------------------------------------------------
Marcos se ABC 898456/L56784 levanta con sueño. | 898456
------------------------------------------------------------------------------------------------- |--------------------------------------------------
Marcos se ABC898456 levanta con sueño. | 898456
------------------------------------------------------------------------------------------------- |--------------------------------------------------
comienza ABC - KE 60014 -T60058 | 60014
------------------------------------------------------------------------------------------------- |--------------------------------------------------
inglés y FOR 102658/L61144 ciencia. Se viste, desayuna | 102658
------------------------------------------------------------------------------------------------- |--------------------------------------------------
y comienza FOR ABC- 72981 / KE T79581: el camino hacia la | 72981
------------------------------------------------------------------------------------------------- |--------------------------------------------------
escuela. Se FOR ABC 101665 - 103035 - 101926 - 105484 - 103036 - 103247 - encuentra con su | [101665,103035,101926,105484,103036,103247]
------------------------------------------------------------------------------------------------- |--------------------------------------------------
escuela ABCS 206048/206049/206050/206051/205225-FG-matemáticas- | [206048,206049,206050,206051,205225]
------------------------------------------------------------------------------------------------- |--------------------------------------------------
encuentra ABCS 111553/L00847 & 111558/L00895 - matemáticas | [111553, 111558]
------------------------------------------------------------------------------------------------- |--------------------------------------------------
ciencia ABC 163278/P20447 AND RETROFIT ABCS 164567/P21000 - 164568/P21001 - desayuna | [163278,164567,164568 ]
------------------------------------------------------------------------------------------------- |--------------------------------------------------
ABC/KE 71729/T81672 - 71781/T81674 71782/T81676 71730/T81673 71783/T81677 71784/T | [71729,71781,71782,71730,71783,71784]
------------------------------------------------------------------------------------------------- |--------------------------------------------------
ciencia ABC/KE2646/L61175:E/F-levanta con sueño L61/62LAV AT Z5CTR/XC D3-1593 | [2646]
-----------------------------------------------------------------------------------------------------------------------------------------------------
escuela ABCS 6048/206049/6050/206051/205225-FG-matemáticas- MSN 2345 | [6048,206049,6050,206051,205225]
-----------------------------------------------------------------------------------------------------------------------------------------------------
FOR ABC/KE 109038_L35674_DEFINE AND DESIGN IMPROVEMENTS OF 1618 FROM 118(PDS4 BRACKETS) | [109038]
-----------------------------------------------------------------------------------------------------------------------------------------------------
y comienza FOR ABC- 2981 / KE T79581: el camino hacia la 9856 | [2981]
我想从该文本中提取包含以下内容的所有数字:4、5 或 6 位数字.提取它们的条件和案例:
I want to extract all numbers that contain: 4, 5 or 6 digits from this text.Condition and cases to extract them:
- Attached to ABC/KE (first line in the example above).
- after ABC/KE + space (second and third line).
- after ABC + space (line 4)
- after ABC without space (line 5)
- after ABC - KE + space
- after for word
- after ABC- + space
- after ABC + space
- after ABCS (line 10 and 11)
失败案例:
Column | new_column
------------------------------------------------------------------------------------------------------------------------
FOR ABC/KE 109038_L35674_DEFINE AND DESIGN IMPROVEMENTS OF 1618 FROM 118(PDS4 BRACKETS) | [1618] ==> should be [109038]
------------------------------------------------------------------------------------------------------------------------
ciencia ABC/KE2646/L61175:E/F-levanta con sueño L61/62LAV AT Z5CTR/XC D3-1593 | [1593] ==> should be [2646]
------------------------------------------------------------------------------------------------------------------------
escuela ABCS 6048/206049/6050/206051/205225-FG-matemáticas- MSN 2345 | [6048,206049,6050,206051,205225, 2345] ==> should be [6048,206049,6050,206051,205225]
我希望我恢复了案例,你可以看到我上面的例子和期望的输出.我该怎么做 ?谢谢
I hope that I resumed the cases, you can see my example above and the expect output.How can I do it ?Thank you
推荐答案
一种使用正则表达式清理数据并设置一个值为 ABC
的单独锚点的方法来识别潜在的开始比赛.在 str.split() 之后,遍历结果数组以标记并检索此锚点后面的连续匹配数字.
One way using regexes to clean out the data and set up a lone anchor with value of ABC
to identify the start of a potential match. after str.split(), iterate through the resulting array to flag and retrieve consecutive matching numbers that follow this anchor.
在数据模式中添加了下划线 _
(\b(\d{4,6})(?=[AZ/_]|$)
) 以便它现在允许下划线作为锚点跟随匹配的 4-6 位子字符串.这修复了第一行、第 2 行和第 3 行应该使用现有的正则表达式模式.
Added underscore _
into the data pattern (\b(\d{4,6})(?=[A-Z/_]|$)
) so that it now allows underscore as an anchor to follow the matched substring of 4-6 digit. this fixed the first line, line 2 and 3 should be working with the existing regex patterns.
import re
from pyspark.sql.types import ArrayType, StringType
from pyspark.sql.functions import udf
(1) 使用正则表达式模式清理原始数据,这样我们就只有一个锚ABC
来识别潜在匹配的开始:
(1) Use regex patterns to clean out the raw data so that we have only one anchor ABC
to identify the start of a potential match:
clean1:使用
[-&\s]+
将 '&'、'-' 和空格转换为 SPACE''
,它们用于连接一串数字
clean1: use
[-&\s]+
to convert '&', '-' and whitespaces to a SPACE' '
, they are used to connect a chain of numbers
example: `ABC - KE` --> `ABC KE`
`103035 - 101926 - 105484` -> `103035 101926 105484`
`111553/L00847 & 111558/L00895` -> `111553/L00847 111558/L00895`
clean2:将符合以下三个子模式的文本转换为'ABC'
clean2: convert text matching the following three sub-patterns into 'ABC '
+ ABCS?(?:[/\s]+KE|(?=\s*\d))
+ ABC followed by an optional `S`
+ followed by at least one slash or whitespace and then `KE` --> `[/\s]+KE`
example: `ABC/KE 110330/L63868` to `ABC 110330/L63868`
+ or followed by optional whitespaces and then at least one digit --> (?=\s*\d)
example: ABC898456 -> `ABC 898456`
+ \bFOR\s+(?:[A-Z]+\s+)*
+ `FOR` words
example: `FOR DEF HJK 12345` -> `ABC 12345`
data:\b(\d{4,6})(?=[AZ/_]|$) 是一个匹配实际的正则表达式数字:4-6 位数字后跟 [AZ/] 或 end_of_string
data: \b(\d{4,6})(?=[A-Z/_]|$) is a regex to match actual numbers: 4-6 digits followed by [A-Z/] or end_of_string
(2) 创建一个 dict 来保存所有 3 个模式:
(2) Create a dict to save all 3 patterns:
ptns = {
'clean1': re.compile(r'[-&\s]+', re.UNICODE)
, 'clean2': re.compile(r'\bABCS?(?:[/\s-]+KE|(?=\s*\d))|\bFOR\s+(?:[A-Z]+\s+)*', re.UNICODE)
, 'data' : re.compile(r'\b(\d{4,6})(?=[A-Z/_]|$)', re.UNICODE)
}
(3) 创建一个函数来查找匹配的数字并将它们保存到数组中
(3) Create a function to find matched numbers and save them into an array
def find_number(s_t_r, ptns, is_debug=0):
try:
arr = re.sub(ptns['clean2'], 'ABC ', re.sub(ptns['clean1'], ' ', s_t_r.upper())).split()
if is_debug: return arr
# f: flag to identify if a chain of matches is started, default is 0(false)
f = 0
new_arr = []
# iterate through the above arr and start checking numbers when anchor is detected and set f=1
for x in arr:
if x == 'ABC':
f = 1
elif f:
new = re.findall(ptns['data'], x)
# if find any matches, else reset the flag
if new:
new_arr.extend(new)
else:
f = 0
return new_arr
except Exception as e:
# only use print in local debugging
print('ERROR:{}:\n [{}]\n'.format(s_t_r, e))
return []
(4) 定义udf函数
(4) defind the udf function
udf_find_number = udf(lambda x: find_number(x, ptns), ArrayType(StringType()))
(5) 获取 new_column
(5) get the new_column
df.withColumn('new_column', udf_find_number('column')).show(truncate=False)
+------------------------------------------------------------------------------------------+------------------------------------------------+
|column |new_column |
+------------------------------------------------------------------------------------------+------------------------------------------------+
|Hoy es da de ABC/KE98789T983456 clase. |[98789] |
|Como ABC/KE 34562Z845673 todas las ma?anas |[34562] |
|Hoy tiene ABC/KE 110330/L63868 clase de matem篓垄ticas, |[110330] |
|Marcos se ABC 898456/L56784 levanta con sue?o. |[898456] |
|Marcos se ABC898456 levanta con sue?o. |[898456] |
|comienza ABC - KE 60014 -T60058 |[60014] |
|ingl篓娄s y FOR 102658/L61144 ciencia. Se viste, desayuna |[102658] |
|y comienza FOR ABC- 72981 / KE T79581: el camino hacia la |[72981] |
|escuela. Se FOR ABC 101665 - 103035 - 101926 - 105484 - 103036 - 103247 - encuentra con su|[101665, 103035, 101926, 105484, 103036, 103247]|
|escuela ABCS 206048/206049/206050/206051/205225-FG-matem篓垄ticas- |[206048, 206049, 206050, 206051, 205225] |
|encuentra ABCS 111553/L00847 & 111558/L00895 - matem篓垄ticas |[111553, 111558] |
|ciencia ABC 163278/P20447 AND RETROFIT ABCS 164567/P21000 - 164568/P21001 - desayuna |[163278, 164567, 164568] |
|ABC/KE 71729/T81672 - 71781/T81674 71782/T81676 71730/T81673 71783/T81677 71784/T |[71729, 71781, 71782, 71730, 71783, 71784] |
+------------------------------------------------------------------------------------------+------------------------------------------------+
(6) 调试代码,使用 find_number(row.column, ptns, 1)
检查前两个正则表达式模式如何/是否按预期工作:
(6) code for debugging, use find_number(row.column, ptns, 1)
to check how/if the first two regex patterns work as expected:
for row in df.limit(10).collect():
print('{}:\n {}\n'.format(row.column, find_number(row.column, ptns)))
一些注意事项:
在
clean2
模式中,ABCS和ABS的处理方式相同.如果它们不同,只需删除S"并在模式末尾添加一个新的替代ABCS\s*(?=\d)
in
clean2
pattern, ABCS and ABS are treated the same way. if they are different, just remove the 'S' and add a new alternativeABCS\s*(?=\d)
to the end of the pattern
re.compile(r'\bABC(?:[/\s-]+KE|(?=\s*\d))|\bFOR\s+(?:[A-Z]+\s+)*|ABCS\s*(?=\d)')
当前模式 clean1
只处理 '-', '&'和空格作为连续连接符,您可以添加更多字符或单词,例如and"、or",例如:
current pattern clean1
only treats '-', '&' and whitespaces as consecutive connector, you might add more characters or words like 'and', 'or', for example:
re.compile(r'[-&\s]+|\b(?:AND|OR)\b')
FOR words
是\bFOR\s+(?:[AZ]+\s+)*,这可能会根据单词等中是否允许数字进行调整.
FOR words
is \bFOR\s+(?:[A-Z]+\s+)*, this might be adjusted based on if numbers are allowed in words etc.
这是在 Python-3 上测试的.使用 Python-2,unicode 可能有问题,您可以使用 参考
This was tested on Python-3. using Python-2, there might be issue with unicode, you can fix it by using the method in the first answer of reference
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