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|
+--------------------+-----+
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]+)
# 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.