如何遍历数据框的列？

Question

我想浏览数据框的所有列。这样我将获得该列的特定数据，使用这些数据我必须为另一个数据帧计算。 我有：

                         DP1         DP2         DP3         DP4         DP5         DP6         DP7         DP8        DP9       DP10       Total
OP1                  357848.0   1124788.0   1735330.0   2218270.0   2745596.0   3319994.0   3466336.0   3606286.0  3833515.0  3901463.0   3901463.0
OP2                  352118.0   1236139.0   2170033.0   3353322.0   3799067.0   4120063.0   4647867.0   4914039.0  5339085.0        NaN   5339085.0
OP3                  290507.0   1292306.0   2218525.0   3235179.0   3985995.0   4132918.0   4628910.0   4909315.0        NaN        NaN   4909315.0
OP4                  310608.0   1418858.0   2195047.0   3757447.0   4029929.0   4381982.0   4588268.0         NaN        NaN        NaN   4588268.0
OP5                  443160.0   1136350.0   2128333.0   2897821.0   3402672.0   3873311.0         NaN         NaN        NaN        NaN   3873311.0
OP6                  396132.0   1333217.0   2180715.0   2985752.0   3691712.0         NaN         NaN         NaN        NaN        NaN   3691712.0
OP7                  440832.0   1288463.0   2419861.0   3483130.0         NaN         NaN         NaN         NaN        NaN        NaN   3483130.0
OP8                  359480.0   1421128.0   2864498.0         NaN         NaN         NaN         NaN         NaN        NaN        NaN   2864498.0
OP9                  376686.0   1363294.0         NaN         NaN         NaN         NaN         NaN         NaN        NaN        NaN   1363294.0
OP10                 344014.0         NaN         NaN         NaN         NaN         NaN         NaN         NaN        NaN        NaN    344014.0
Total               3671385.0  11614543.0  17912342.0  21930921.0  21654971.0  19828268.0  17331381.0  13429640.0  9172600.0  3901463.0  34358090.0
Latest Observation   344014.0   1363294.0   2864498.0   3483130.0   3691712.0   3873311.0   4588268.0   4909315.0  5339085.0  3901463.0         NaN 

从这个表我想计算公式这个公式：在 DP1 列，总/最后一次观察中，这个答案是除以 DP2 列总数。像这样，我们必须计算所有列并将其保存在另一个数据框中。

我们需要这样的行：

Weighted Average     3.491   1.747   1.457   1.174   1.104   1.086   1.054   1.077   1.018 

我们尝试过的这段代码：

LDFTriangledf['Weighted Average'] =CumulativePaidTriangledf.loc['Total','DP2']/(CumulativePaidTriangledf.loc['Total','DP1'] - CumulativePaidTriangledf.loc['Latest Observation','DP1'])

Answer 1

您可以从.loc 中删除列名，只删除shift(-1, axis=1) 以获取下一列的Total。这使您可以在一次操作中将公式应用于所有列：

CumulativePaidTriangledf.shift(-1, axis=1).loc['Total'] / (CumulativePaidTriangledf.loc['Total'] - CumulativePaidTriangledf.loc['Latest Observation'])

# DP1      3.490607
# DP2      1.747333
# DP3      1.457413
# DP4      1.173852
# DP5      1.103824
# DP6      1.086269
# DP7      1.053874
# DP8      1.076555
# DP9      1.017725
# DP10          inf
# Total         NaN
# dtype: float64

---

以下是这三个组件的功能细分：

	DP1	DP2	DP3	DP4	DP5	DP6	DP7	DP8	DP9	DP10	Total
A: .shift(-1, axis=1).loc['Total'] -- We are shifting the whole Total row to the left, so every column now has the next Total value.	1.161454e+07	1.791234e+07	2.193092e+07	2.165497e+07	1.982827e+07	1.733138e+07	1.342964e+07	9.172600e+06	3.901463e+06	34358090.0	NaN
B: .loc['Total'] -- This is the normal Total row.	3.671385e+06	1.161454e+07	1.791234e+07	2.193092e+07	2.165497e+07	1.982827e+07	1.733138e+07	1.342964e+07	9.172600e+06	3901463.0	34358090.0
C: .loc['Latest Observation'] -- This is the normal Latest Observation.	3.440140e+05	1.363294e+06	2.864498e+06	3.483130e+06	3.691712e+06	3.873311e+06	4.588268e+06	4.909315e+06	5.339085e+06	3901463.0	NaN
A / (B-C) -- This is what the code above does. It takes the shifted Total row (A) and divides it by the difference of the current Total row (B) and current Latest observation row (C).	3.490607	1.747333	1.457413	1.173852	1.103824	1.086269	1.053874	1.076555	1.017725	inf	NaN