我有如下数据,我正在尝试将数据分组为日期和时间。
[
{
"avg": 52,
"hour": 9,
"dayname": "Friday"
},
{
"avg": 1,
"hour": 10,
"dayname": "Friday"
},
{
"avg": 12,
"hour": 11,
"dayname": "Friday"
},
{
"avg": 3,
"hour": 12,
"dayname": "Friday"
},
{
"avg": 12,
"hour": 09,
"dayname": "Saturday"
},
{
"avg": 30,
"hour": 10,
"dayname": "Saturday"
},
{
"avg": 66,
"hour": 11,
"dayname": "Saturday"
},
{
"avg": 45,
"hour": 12,
"dayname": "Saturday"
}
]
我想要最终的 OP:
hour Friday Saturday
9 52 12
10 1 30
11 12 16
12 3 45
这是我尝试过的代码:
cur = mysql.connection.cursor()
sql = "select avg(value) avg, hour, dayname from table;"
cur.execute(sql)
row_headers = [x[0] for x in cur.description] #this will extract row headers
rv = cur.fetchall()
json_result = []
for result in rv:
json_result.append(dict(zip(row_headers, result)))
# resultfromdb= json.dumps(json_result)
finalresult = #how to get the expected op
return finalresult
从那里如何使用 pandas 进行分组并获得最终结果?
最佳答案
您可以将 DataFrame
构造函数与 groupby
一起使用,聚合 sum
并按 unstack
reshape :
df = (pd.DataFrame(lst)
.groupby(['hour','dayname'])['avg']
.sum()
.unstack(fill_value=0)
.rename_axis(None, 1)
.reset_index())
print (df)
hour Friday Saturday
0 9 52 12
1 10 1 30
2 11 12 66
3 12 3 45
关于python - Pandas 在字典列表中分组,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/50040989/