group function in sql
--- GROUP FUNCTION | MULTI ROW FUNCTION | AGGREGATE FUNCTION
--- COUNT , MAX , MIN , SUM , AVGgroup function in sql
--- GROUP FUNCTION | MULTI ROW FUNCTION | AGGREGATE FUNCTION
--- COUNT , MAX , MIN , SUM , AVGgroup by
SELECT
<column_name>,
COUNT(<column_name>) AS `value_occurrence`
FROM
<my_table>
GROUP BY
<column_name>
ORDER BY
`value_occurrence` DESC
LIMIT 1;group by
class groupby(object):
# [k for k, g in groupby('AAAABBBCCDAABBB')] --> A B C D A B
# [list(g) for k, g in groupby('AAAABBBCCD')] --> AAAA BBB CC D
def __init__(self, iterable, key=None):
if key is None:
key = lambda x: x
self.keyfunc = key
self.it = iter(iterable)
self.tgtkey = self.currkey = self.currvalue = object()
def __iter__(self):
return self
def next(self):
while self.currkey == self.tgtkey:
self.currvalue = next(self.it) # Exit on StopIteration
self.currkey = self.keyfunc(self.currvalue)
self.tgtkey = self.currkey
return (self.currkey, self._grouper(self.tgtkey))
def _grouper(self, tgtkey):
while self.currkey == tgtkey:
yield self.currvalue
self.currvalue = next(self.it) # Exit on StopIteration
self.currkey = self.keyfunc(self.currvalue)GROUP BY
SELECT <field1, field2, field3…>
FROM <table1_name>
WHERE <condition/expression>
GROUP BY <field1, field2, field3…>group by data
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
dd=pd.melt(df,id_vars=['Group'],value_vars=['Apple','Orange'],var_name='fruits')
sns.boxplot(x='Group',y='value',data=dd,hue='fruits')Copyright © 2021 Codeinu
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