使用Dataframe保存python for循环中更新的值

我是Python和Pandas的新手，我试图用一个特定的值替换数组中的所有空值

每次我运行它时，更新的值都不会持久

我已经看到Pandas在迭代行时不保存更改…那么如何保存更改呢

这是我的密码

animal_kinds = set(df.AnimalKind) # this gives categories used below in the "ak" like dog, cat, bird
new_color_dog = 'polka dots'
new_color_cat = 'plaid'
new_color_bird = 'stripes'

for ak in animal_kinds:
    ak_colors = ak['colors']


    ak_with_no_color = animals[(df["Kind"] == ak ) & (df["Color"] == "" ) ] 


    result_count = len(ak_with_no_color)
    if result_count:

        ak_with_no_color.at["Color"] = new_color_ak #sets new color based on kind of animal (ak) 
        print(str(ak) 'color is changed to ' + str(new_color_ak))

避免链式索引 这种操作称为链式索引，它是：

df[(df['kind'] == 'dog') & (df['colour'] == '')].at['colour'] = 'black'

相反，请计算并使用布尔掩码：

mask = (df['kind'] == 'dog') & (df['colour'] == '')
df.loc[mask, 'colour'] = 'black'

使用字典查找可变数量的变量 这种操作在Python中不起作用：

new_colour_dog = 'polka dots'
new_colour+'_dog'  # want 'polka dots', but will not work

改用字典：

new_colours = {'dog': 'polka dots', 'cat': 'plaid', 'bird': 'stripes'}

然后可以迭代字典的键值对：

for animal, new_colour in new_colours.items():
    mask = (df['kind'] == animal) & (df['colour'] == '')
    df.loc[mask, 'colour'] = new_colour

当

mask

返回一系列

False

值时，不需要测试/特殊情况实例