行中的筛选器值包含用于进一步计算的特定字符串

Question

这是我的数据帧：

In [2]: fruits = pd.DataFrame({"apple_price": [100, 100, 200, 500, 100, 600, 200], 
   ...:                        "cherry_price": [2, 3, 1, 0, 2, 1, 1], 
   ...:                        "banana_price": [2, 4, 5, 2, 3, 5, 3], 
   ...:                        "prices": ["apple_price", "apple_price", "cherry_price", "banana_price", "cherry_price",
   ...:  "banana_price", "apple_price"], 
   ...:                        "price_fruits": [100, 100, 100, 2, 3, 5, 200]})

In [3]: fruits
Out[3]:
   apple_price  cherry_price  banana_price        prices  price_fruits
0          100             2             2   apple_price           100
1          100             3             4   apple_price           100
2          200             1             5  cherry_price           100
3          500             0             2  banana_price             2
4          100             2             3  cherry_price             3
5          600             1             5  banana_price             5
6          200             1             3   apple_price           200

基本上，苹果的价格必须除以100（因为苹果的价格是美分而不是欧元），而其他水果的价格应该保持不变

这就是我的预期输出：

In [5]: fruits_ad
Out[5]:
   apple_price  cherry_price  banana_price        prices  price_fruits  pr_fruits_adjusted
0          100             2             2   apple_price           100                   1
1          100             3             4   apple_price           100                   1
2          200             1             5  cherry_price           100                   1
3          500             0             2  banana_price             2                   2
4          100             2             3  cherry_price             3                   3
5          600             1             5  banana_price             5                   5
6          200             1             3   apple_price           200                   2

Answer 1

根据条件对价格进行调整可以这样做：

fruits['pr_fruits_adjusted'] = np.where((fruits.price_fruits >=100), fruits['price_fruits']/100, fruits['price_fruits']).astype('int32')

您可以根据需要更改条件。这里我写了一个条件，如果价格大于或等于100，则进行调整。 fruits.price_fruits >=100

Answer 2

抱歉，伙计们，我太匆忙了，把我的示例数据框搞砸了

你看，伙计：

你从这里开始

In [2]: fruits = pd.DataFrame({"Variety": ["apple_price", "cherry_price", "banana_price", "apple_price", "banana_price"
   ...: ], 
   ...:                        "Price": [100, 2, 3, 200, 3]})

In [3]: fruits
Out[3]:
        Variety  Price
0   apple_price    100
1  cherry_price      2
2  banana_price      3
3   apple_price    200
4  banana_price      3

这应该是预期的输出：

In [4]: fruits_adj = pd.DataFrame({"Variety": ["apple_price", "cherry_price", "banana_price", "apple_price", "banana_pr
   ...: ice"], ^M
   ...:                            "Price": [100, 2, 3, 200, 3], ^M
   ...:                            "Price_Adj": [1, 2, 3, 2, 3]})

In [5]: fruits_adj
Out[5]:
        Variety  Price  Price_Adj
0   apple_price    100          1
1  cherry_price      2          2
2  banana_price      3          3
3   apple_price    200          2
4  banana_price      3          3

简而言之，我要查找的代码将字符串拆分为“Variance”列，并检查我是否包含“apple”，如果此条件==True，则应将apple_价格除以100，否则从“price”列中获取相应水果的价格

这是我的尝试也许你有更优雅的东西：

In [6]: chk = fruits_adj['Variety'].str.contains(r'apple', na=True)

In [7]: fruits.loc[chk, "Price_Adj"] = fruits["Price"] / 100

In [8]: fruits.loc[~chk, "Price_Adj"] = fruits["Price"]

In [9]: fruits
Out[9]:
        Variety  Price  Price_Adj
0   apple_price    100        1.0
1  cherry_price      2        2.0
2  banana_price      3        3.0
3   apple_price    200        2.0
4  banana_price      3        3.0

干杯 类风湿关节炎