如何使用正则表达式替换值

时间:2019-06-13 03:40:12

标签: apache-spark pyspark apache-spark-sql pyspark-sql

我有一个具有列名和比率的数据框,我想计算比率大于4.0的名称数

+--------------------+-----+
|                name| rate|
+--------------------+-----+
|               Jalsa|4.1/5|
|      Spice Elephant|4.1/5|
|     San Churro Cafe|3.8/5|
|Addhuri Udupi Bho...|3.7/5|
|       Grand Village|3.8/5|
+--------------------+-----+

2 个答案:

答案 0 :(得分:1)

假设df是您的数据框,

from pyspark.sql import functions as F
# First, you filter your lines
df_filtered = df.where(F.split(F.col("rate"), '/').getItem(0).cast("double") > 4.0)

# Then, you count
df_filtered.count()
> 2

答案 1 :(得分:-1)

此表达式将输出我们想要的数字,然后您可以简单地进行数学计算:

([0-9.]+)\/([0-9]+)

Demo

测试

# coding=utf8
# the above tag defines encoding for this document and is for Python 2.x compatibility

import re

regex = r"([0-9.]+)\/([0-9]+)"

test_str = ("+--------------------+-----+\n"
    "|                name| rate|\n"
    "+--------------------+-----+\n"
    "|               Jalsa|4.1/5|\n"
    "|      Spice Elephant|4.1/5|\n"
    "|     San Churro Cafe|3.8/5|\n"
    "|Addhuri Udupi Bho...|3.7/5|\n"
    "|       Grand Village|3.8/5|\n"
    "+--------------------+-----+\n")

matches = re.finditer(regex, test_str, re.MULTILINE)

for matchNum, match in enumerate(matches, start=1):

    print ("Match {matchNum} was found at {start}-{end}: {match}".format(matchNum = matchNum, start = match.start(), end = match.end(), match = match.group()))

    for groupNum in range(0, len(match.groups())):
        groupNum = groupNum + 1

        print ("Group {groupNum} found at {start}-{end}: {group}".format(groupNum = groupNum, start = match.start(groupNum), end = match.end(groupNum), group = match.group(groupNum)))

# Note: for Python 2.7 compatibility, use ur"" to prefix the regex and u"" to prefix the test string and substitution.