问题

以下是您要的翻译内容：

In Python I have to build a (long) if statement dynamically.
How can I do this?

我需要在Python中动态构建一个（较长的）if语句。
我该如何做？

I tried the following test code to store the necessary if-statement within a string with the function "buildFilterCondition".
But this doesn't work...

我尝试了以下测试代码，使用函数"buildFilterCondition"将必要的if语句存储在字符串中。但这并不起作用...

Any ideas? What is going wrong?
Thank you very much.

有什么想法吗？出了什么问题？
非常感谢。

Input = [1,2,3,4,5,6,7]
Filter = [4,7]
FilterCondition = ""

Input = [1,2,3,4,5,6,7]
Filter = [4,7]
FilterCondition = ""

def buildFilterCondition():
global FilterCondition
for f in Filter:
FilterCondition = FilterCondition + "(x==" + str(f) + ") | "

#remove the last "| " sign
FilterCondition = FilterCondition[:-2]
print("Current Filter: " + FilterCondition)

buildFilterCondition()
for x in Input:
if( FilterCondition ):
print(x)

def buildFilterCondition():
global FilterCondition
for f in Filter:
FilterCondition = FilterCondition + "(x==" + str(f) + ") | "

#移除最后的"| "符号
FilterCondition = FilterCondition[:-2]
print("当前过滤条件: " + FilterCondition)

buildFilterCondition()
for x in Input:
if( FilterCondition ):
print(x)

With my Function buildFilterCondition() I want to reach the following situation, because the function generates the string "(x==4) | (x==7)", but this doesn't work:

使用我的函数buildFilterCondition()，我想达到以下情况，因为该函数生成字符串"(x==4) | (x==7)"，但这不起作用：

for x in Input:
if( (x==4) | (x==7) ):
print(x)

The output, the result should be 4,7 (--> filtered)

输出，结果应该是4,7（-->已过滤）

The background of my question actually had a different intention than to replace an if-statement.

我的问题的背景实际上有一个不同的意图，不是要替代if语句。

I need a longer multiple condition to select specific columns of a pandas dataframe.

我需要一个更长的多重条件来选择pandas数据框的特定列。

For example:

例如：

df2=df.loc[(df['Discount1'] == 1000) & (df['Discount2'] == 2000)]

df2=df.loc[(df['Discount1'] == 1000) & (df['Discount2'] == 2000)]

I wanted to keep the column names and the values (1000, 2000) in 2 separate lists (or dictionary) to make my code a little more "generic".

我想将列名和值（1000、2000）分别保存在两个列表（或字典）中，以使我的代码更加“通用”。

colmnHeader = ["Discount1", "Discount2"]
filterValue = [1000, 2000]

colmnHeader = ["Discount1", "Discount2"]
filterValue = [1000, 2000]

To "filter" the data frame, I then only need to adjust the lists.

然后，我只需要调整列表来“过滤”数据框。

How do I now rewrite the call to the .loc method so that it works for iterating over the lists?

现在，我该如何重写对.loc方法的调用，以使其适用于对列表进行迭代？

df2=df.loc[(df[colmnHeader[0] == [filterValue[0]) & (df[colmnHeader[1]] == filterValue[1])]

df2=df.loc[(df[colmnHeader[0] == [filterValue[0]) & (df[colmnHeader[1]] == filterValue[1])]

Unfortunately, my current attempt with the following code does not work because the panda-loc function has not to be called sequentially, but in parallel.

不幸的是，我的当前尝试与以下代码不起作用，因为pandas的.loc函数不需要按顺序调用，而是并行调用。

#FILTER
colmn = ["colmn1", "colmn2", "colmn3"]
cellContent = ["1000", "2000", "3000"]

first make sure, the lists have the same size

if( len(colmn) == len(cellContent)):
curIdx = 0
for curColmnName in colmn:
df_columns= df_columns.loc[df_columns [curColmnName]==cellContent[curIdx]]
curIdx += 1

#筛选
colmn = ["colmn1", "colmn2", "colmn3"]
cellContent = ["1000", "2000", "3000"]

#首先确保列表具有相同的大小
if( len(colmn) == len(cellContent)):
curIdx = 0
for curColmnName in colmn:
df_columns= df_columns.loc[df_columns [curColmnName]==cellContent[curIdx]]
curIdx += 1

Thank you again!

再次感谢！

Input = [1,2,3,4,5,6,7]
Filter = [4,7]
FilterCondition = ""

def buildFilterCondition():
    global FilterCondition
    for f in Filter:
        FilterCondition = FilterCondition + "(x==" + str(f) +") | "

    #remove the last "| " sign
    FilterCondition = FilterCondition[:-2]
    print("Current Filter: " + FilterCondition)



buildFilterCondition()
for x in Input:
    if( FilterCondition ):
        print(x)

for x in Input:
    if( (x==4) | (x==7) ):
        print(x)

df2=df.loc[(df['Discount1'] == 1000) & (df['Discount2'] == 2000)]

colmnHeader = ["Discount1", "Discount2"]
filterValue = [1000, 2000]

df2=df.loc[(df[colmHeader[0] == [filterValue[0]) & (df[colmHeader[1]] == filterValue[1])]

#FILTER
colmn = ["colmn1", "colmn2", "colmn3"]
cellContent = ["1000", "2000", "3000"]

# first make sure, the lists have the same size
if( len(colmn) == len(cellContent)):
    curIdx = 0
    for curColmnName in colmn:
        df_columns= df_columns.loc[df_columns [curColmnName]==cellContent[curIdx]]
        curIdx += 1

答案1

得分: 2

使用 in 运算符

因为简单胜于复杂。

inputs = [1, 2, 3, 4, 5, 6, 7]
value_filter = [4, 7]

for x in inputs:
    if x in value_filter:
        print(x, end=' ')
# 4 7

inputs = [1, 2, 3, 4, 5, 6, 7]
value_filter = [4, 7]

for x in inputs:
    if x in value_filter:
        print(x, end=' ')
# 4 7

答案2

得分: 1

使用operator模块

使用operator模块，您可以在运行时构建一个条件，该条件由操作符和值对的列表组成，用于测试当前值。

import operator

inputs = [1, 2, 3, 4, 5, 6, 7]

# 如果需要，可以动态更改此列表
conditions = [
    (operator.ge, 4),  # 值需要大于或等于4
    (operator.lt, 7),  # 值需要小于7
]

for x in inputs:
    # 使用all来对所有条件应用and运算符，使用any来应用or运算符
    if all(condition(x, value) for condition, value in conditions):
        print(x, end=' ')

# 4 5 6

import operator

inputs = [1, 2, 3, 4, 5, 6, 7]

# This list can be dynamically changed if you need to
conditions = [
    (operator.ge, 4),  # value need to be greater or equal to 4
    (operator.lt, 7),  # value need to be lower than 7
]

for x in inputs:
    # all to apply a and operator on all condition, use any for or
    if all(condition(x, value) for condition, value in conditions):
        print(x, end=' ')

# 4 5 6