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Accepted
Yuriy Tigiev
Asked:2021-11-10 16:06:39 +0000 UTC2021-11-10 16:06:39 +0000 UTC

统计DataFrame列中非空值的个数，使用单行表达式将结果保存到同一张表中

  • 772

如何使用单行表达式计算列中非空值的数量，并将结果写入相同的列而不是非空值？

import pandas as pd 
import numpy as np 
import matplotlib.pyplot as plt
import seaborn as sns


sns.set()

d = {
     7:{"c1":5, "c2":8, "c3":10},
     5:{"c1":1, "c2":7, "c3":10}, 
     4:{"c1":1, "c2":6, "c3":8}, 
     3:{"c1":4, "c2":7, "c3":9},
     2:{"c1":3, "c2":5, "c3":6},
     1:{"c1":2, "c2":7, "c3":9}
    }

df = pd.DataFrame(d).T
r = (df
     .stack()
     .reset_index(name="col")
     .assign(x=1)
     .pivot_table(index="level_0", columns="col", values="x")
     .reindex(range(1,11), axis=1)
     .fillna(0)
     .astype("int8")
     .rename_axis(None)
     .rename_axis(None, axis=1))

print(r)

当前结果

   1  2  3  4  5  6  7  8  9  10
1  0  1  0  0  0  0  1  0  1   0
2  0  0  1  0  1  1  0  0  0   0
3  0  0  0  1  0  0  1  0  1   0
4  1  0  0  0  0  1  0  1  0   0
5  1  0  0  0  0  0  1  0  0   1
7  0  0  0  0  1  0  0  1  0   1

预期结果

   1  2  3  4  5  6  7  8  9  10
1  0  1  0  0  0  0  3  0  2   0
2  0  0  1  0  2  2  0  0  0   0
3  0  0  0  1  0  0  3  0  2   0
4  2  0  0  0  0  2  0  2  0   0
5  2  0  0  0  0  0  3  0  0   2
7  0  0  0  0  2  0  0  2  0   2
python

1 个回答

  1. Best Answer
    import pandas as pd 

d = {
     7:{"c1":5, "c2":8, "c3":10},
     5:{"c1":1, "c2":7, "c3":10}, 
     4:{"c1":1, "c2":6, "c3":8}, 
     3:{"c1":4, "c2":7, "c3":9},
     2:{"c1":3, "c2":5, "c3":6},
     1:{"c1":2, "c2":7, "c3":9}
    }
df = pd.DataFrame(d).T
print(df)
r = (df
     .stack()
     .reset_index(name="col")
     .assign(x=1)
     .pivot_table(index="level_0", columns="col", values="x")
     .reindex(range(1,11), axis=1)
     .fillna(0)
     .astype("int8")
     .rename_axis(None)
     .rename_axis(None, axis=1)).apply(lambda x: x*sum(x))
print(r)

       1  2  3  4  5  6  7  8  9  10
1  0  1  0  0  0  0  3  0  2   0
2  0  0  1  0  2  2  0  0  0   0
3  0  0  0  1  0  0  3  0  2   0
4  2  0  0  0  0  2  0  2  0   0
5  2  0  0  0  0  0  3  0  0   2
7  0  0  0  0  2  0  0  2  0   2

    如果您需要更通用的选项（当数据帧中的非零值不一定等于 1 时，那么apply最好将后者写成这样：

    .apply(lambda x: x.astype("bool")*sum(x.astype("bool")))
    • 2

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