pandas.core.base.DataError: No numeric types to aggregate錯誤規避

我沒有去解決這個問題, 而用填充0規避了這個問題

統計 聚合

d = [
    {'cur': 1, 'next': 2, 'avgtime': None, 'callcount': None},
    {'cur': 2, 'next': 3, 'avgtime': None, 'callcount': None},
    {'cur': 2, 'next': 4, 'avgtime': None, 'callcount': None},

    {'cur': 1, 'next': 2, 'avgtime': None, 'callcount': None},
    {'cur': 2, 'next': 3, 'avgtime': None, 'callcount': None},
    {'cur': 2, 'next': 4, 'avgtime': None, 'callcount': None},

    {'cur': None, 'next': 4, 'avgtime': None, 'callcount': None},
]

df = pd.DataFrame(d, dtype='int')
df.groupby(["cur", "next"], as_index=False).mean()
 

agg函式

使用這種聚合會卡到這個bug
pandas.core.base.DataError: No numeric types to aggregate錯誤規避

import pandas as pd

d = [
    {'cur': 1, 'next': 2, 'avgtime': None, 'callcount': None},
    {'cur': 2, 'next': 3, 'avgtime': None, 'callcount': None},
    {'cur': 2, 'next': 4, 'avgtime': None, 'callcount': None},

    {'cur': 1, 'next': 2, 'avgtime': None, 'callcount': None},
    {'cur': 2, 'next': 3, 'avgtime': None, 'callcount': None},
    {'cur': 2, 'next': 4, 'avgtime': None, 'callcount': None},

    {'cur': None, 'next': 4, 'avgtime': None, 'callcount': None},
]

df = pd.DataFrame(d, dtype='int')
g = df.groupby(["cur", "next"], as_index=False)
res = g.agg(
    {
        'avgtime': 'sum',
        'callcount': 'mean',
    }
)