将嵌套if语句应用于df_python

以下代码必须执行一些步骤：

如果“批发数据”列的使用率大于等于“ mbs”列
减去“批发数据”列-“ mbs”
根据下表乘以差异
- 32-0.56
- 64-0.5
- 128-0.4
- 256-0.4
- 512-0.3
- 1024-0.3
对于所有其他可能的选项-0

我有以下代码

if df['Wholesale Data Usage'] >= df['mbs']:
    if df['mbs'] == "32":
        df['Additional Charge'] = (df['Wholesale Data Usage'] - df[
        'mbs']) * 0.5
    elif df['mbs'] == "64":
        df['Additional Charge'] = (df['Wholesale Data Usage'] - df[
        'mbs']) * 0.5
    elif df['mbs'] == "128":
        df['Additional Charge'] = (df['Wholesale Data Usage'] - df[
        'mbs']) * 0.4
    elif df['mbs'] == "256":
        df['Additional Charge'] = (df['Wholesale Data Usage'] - df[
        'mbs']) * 0.4
    elif df['mbs'] == "512":
        df['Additional Charge'] = (df['Wholesale Data Usage'] - df[
        'mbs']) * 0.3
    elif df['mbs'] == "1024":
        df['Additional Charge'] = (df['Wholesale Data Usage'] - df[
        'mbs']) * 0.3
    else:
        df['Additional Charge'] = 0
else:
    df['Additional Charge'] = 0

不知道我在做什么错。

首先，对于32，您乘以0.5，而不是0.56。

然后，似乎您已经混淆了Strings和Integers 。 如果df['Wholesale Data Usage']和df['mbs']存储的数据的类型为String，则您不能检查大于（ >= ），也不能从中减去一个。

我怀疑存储在字典中的数据是Integer或Float或Double类型的。 在这种情况下，您尝试将数据与字符串进行比较，并应更改以下内容：

if df['mbs'] == "32":

至：

if df['mbs'] == 32:

并在每次比较时都这样做

您的代码是如此难以阅读，难以调试。 编码样式将帮助您查看自己认为的错误。 如果你这样写怎么办？

mbs = df['mbs']
wdu = df['Wholesale Data Usage']

ac = 0
if wdu >= mbs and mbs == "32"   : ac = (wdu - mbs) * 0.56
if wdu >= mbs and mbs == "64"   : ac = (wdu - mbs) * 0.5
if wdu >= mbs and mbs == "128"  : ac = (wdu - mbs) * 0.4
if wdu >= mbs and mbs == "256"  : ac = (wdu - mbs) * 0.4
if wdu >= mbs and mbs == "512"  : ac = (wdu - mbs) * 0.3
if wdu >= mbs and mbs == "1024" : ac = (wdu - mbs) * 0.3

df['Additional Charge'] = ac

话虽这么说，您有类型问题。 我正在比较的第一个等式mbs=="32"好像您有一个字符串。 然后在方程式中尝试添加值，就好像它们包含一个int一样-这将无法工作。 让类型变得合理。

mbs = float(df['mbs'])
wdu = float(df['Wholesale Data Usage'])

ac = 0
if wdu >= mbs and mbs == 32   : ac = (wdu - mbs) * 0.56
if wdu >= mbs and mbs == 64   : ac = (wdu - mbs) * 0.5
if wdu >= mbs and mbs == 128  : ac = (wdu - mbs) * 0.4
if wdu >= mbs and mbs == 256  : ac = (wdu - mbs) * 0.4
if wdu >= mbs and mbs == 512  : ac = (wdu - mbs) * 0.3
if wdu >= mbs and mbs == 1024 : ac = (wdu - mbs) * 0.3

df['Additional Charge'] = str(ac) #<- you need to know what the expected type is here.

我认为您的逻辑以及代码逐步通过逻辑的方式存在一些问题，例如，您检查mbs列是否等于32，但实际上应该是“ Wholesale Data Usage列与mbs栏等于32。

这应该可以解决您的逻辑问题，而无需编辑过多的代码：

df['mbs'] = np.where(df['Wholesale Data Usage'] >= df['mbs'], df['Wholesale Data Usage']-df['mbs'], 0)

if df['mbs'] == "32":
    df['Additional Charge'] = (df['mbs']) * 0.5
elif df['mbs'] == "64":
    df['Additional Charge'] = (df['mbs']) * 0.5
elif df['mbs'] == "128":
    df['Additional Charge'] = (df['mbs']) * 0.4
elif df['mbs'] == "256":
    df['Additional Charge'] = (df['mbs']) * 0.4
elif df['mbs'] == "512":
    df['Additional Charge'] = (df['mbs']) * 0.3
elif df['mbs'] == "1024":
    df['Additional Charge'] = (df['mbs']) * 0.3
else:
    df['Additional Charge'] = 0

将嵌套if语句应用于df

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