Question

我有一个分组和聚合的数据框

df_subsegment:
    segment         Sales   Income  Rent
0   A               184.37  224.24  5242.9  
1   B               45.42   176.79  6693.0  
<+100 rows>

我已经从上述数据框中创建了一个列表：

    SubSegment_list = df_subsegment['segment'].unique()
    SubSegment_list

[out] array(['A', 'B'], dtype=object)


for i in SubSegment_list:
    var1 = df['Sales']
    var2 = df['Income']
    var3 = df['Rent']
    flag1 = 'up' if var1>0 else 'down'
    flag2 = 'up' if var2>0 else 'down'
    flag3 = 'leverage' if var3>0 else 'deleverage'
    print(f"{SubSegment_list[0]} Sales {flag1} {round(var1)} % vs LY while Total income {flag2} {var2}% vs LY creating {flag3}")

让我们考虑一下，上面提到的列表现在只有2个值，即A和B。然后从此for循环中萌发的输出包含两个语句，但是它们都具有相同的值，如下所示：

A Sales up 184 % vs LY while Total income up 224.24% vs LY creating leverage
A Sales up 184 % vs LY while Total income up 224.24% vs LY creating leverage

如何考虑每行的数据生成两个唯一的语句，如下所示：

预期输出：

A Sales up 184% vs LY while Total income up 224.24% vs LY creating leverage
B Sales up 45% vs LY while Total income up 176.79% vs LY creating leverage

Answer 1

您可以使用iterrows：

for _, value in df.iterrows():

    var1 = value['Sales']
    var2 = value['Income']

    seg1 = value['segment']

    flag1 = 'up' if var1>0 else 'down'
    flag2 = 'up' if var2>0 else 'down'

    print(f"{seg1} Sales {flag1} {var1}% vs LY while Total income {flag2} {var2}% vs LY creating leverage")

A Sales up 184.37% vs LY while Total income up 224.24% vs LY creating leverage
B Sales up 45.42% vs LY while Total income up 176.79% vs LY creating leverage

在熊猫数据框上使用for循环生成唯一语句

1 个答案: