Python break down a super long IF statement

问题

How to simplify or break down the super long IF Condition in Python pandas?

my_dataframes = {'d1': d1, 'd2': d2,'d3': d3}
good_dataframes = []
for df_name, df in my_dataframes.items():
    if ((df.loc[1:4, 'test'] <= 6).all() 
        and (df.loc[5:9, 'dif'] < 9).all()) or ((df.loc[1:5, 'test'] <= 6).all() 
                                                      and (df.loc[5:8, 'dif'] < 8).all()) or ((df.loc[1:8, 'test'] <= 6).all() 
                                                                                                    and (df.loc[5:8, 'dif'] < 9).all()):
        good_dataframes.append(df_name)

the challenge for me is put the right indent

回答1:

you can break down in 3 major check functions:

my_dataframes = {'d1': d1, 'd2': d2,'d3': d3}

def check_1(df):
    return (df.loc[1:4, 'test'] <= 6).all() and (df.loc[5:9, 'dif'] < 9).all()

def check_2(df):
    return (df.loc[1:5, 'test'] <= 6).all() and (df.loc[5:8, 'dif'] < 8).all()

def check_3(df):
    return (df.loc[1:8, 'test'] <= 6).all() and (df.loc[5:8, 'dif'] < 9).all()

CHECK_FUNCTIONS = (check_1, check_2, check_3)

def check(df):
    return any(check_f(df) for check_f in CHECK_FUNCTIONS)

good_dataframes = []
for df_name, df in my_dataframes.items():

    if  check(df):
        good_dataframes.append(df_name)

to obtain good_dataframes you can use a list comprehension:

good_dataframes = [df_name for df_name, df in my_dataframes.items() if check(df)]

回答2:

Define a function that contains the conditions.

def is_good_df(df):
    return (((df.loc[1:4, 'test'] <= 6).all()
             and (df.loc[5:9, 'dif'] < 9).all())
            or ((df.loc[1:5, 'test'] <= 6).all()
                and (df.loc[5:8, 'dif'] < 8).all())
            or ((df.loc[1:8, 'test'] <= 6).all()
                and (df.loc[5:8, 'dif'] < 9).all()))

A good IDE should help with getting the indentation right.

Notice that you were also missing the () after some of your .all calls.

Then you can do

my_dataframes = {'d1': d1, 'd2': d2,'d3': d3}
good_dataframes = [df_name for df, df_name in my_dataframes.items() if is_good_df(df)]

回答3:

would this make it more understandable:

my_dataframes = {'d1': d1, 'd2': d2,'d3': d3}
good_dataframes = []
for df_name, df in my_dataframes.items():
    if ((df.loc[1:4, 'test'] <= 6).all and (df.loc[5:9, 'dif'] < 9).all()) or 
       ((df.loc[1:5, 'test'] <= 6).all and (df.loc[5:8, 'dif'] < 8).all()) or 
       ((df.loc[1:8, 'test'] <= 6).all and (df.loc[5:8, 'dif'] < 9).all()):
        good_dataframes.append(df_name)

回答4:

You can put your and expressions in a list and then check if any of the values is True (matches with your or logic):

my_dataframes = {'d1': d1, 'd2': d2,'d3': d3}
good_dataframes = []
for df_name, df in my_dataframes.items():
    conds = [(df.loc[1:4, 'test'] <= 6).all and (df.loc[5:9, 'dif'] < 9).all(),
             (df.loc[1:5, 'test'] <= 6).all and (df.loc[5:8, 'dif'] < 8).all(),
             (df.loc[1:8, 'test'] <= 6).all and (df.loc[5:8, 'dif'] < 9).all()]
    if any(conds):
        good_dataframes.append(df_name)

回答5:

You can use the logical operation like and, or etc.

`my_dataframes = {'d1': d1, 'd2': d2,'d3': d3} good_dataframes = [] for df_name, df in my_dataframes.items():
    conds = [(df.loc[1:4, 'test'] <= 6).all and (df.loc[5:9, 'dif'] < 9).all(),
             (df.loc[1:5, 'test'] <= 6).all and (df.loc[5:8, 'dif'] < 8).all(),
             (df.loc[1:8, 'test'] <= 6).all and (df.loc[5:8, 'dif'] < 9).all()]
    if any(conds):
        good_dataframes.append(df_name)

来源：https://stackoverflow.com/questions/59586706/python-break-down-a-super-long-if-statement

标签

python

python-3.x

pandas

if-statement