AIA 20200527 python 小考

#第1題

cx = [1, 3, 5, 7, 2, 1, 8]

def less_than_5(array):

    y = []

    for i in array:

        if i < 5:

            y.append(i)

    return y

print(less_than_5(x))

#第2題

factory1 = {"條件1" :    30, "條件2" : 10, "溫度容許值" : 20}

factory2 = {"條件1" : 48763, "條件3" : 75, "溫度容許值" : 60}

def dict_merge_with_bigger(Dict1, Dict2):

    ND = Dict1

    for key in Dict2:

        if ND.get(key):

            if Dict2[key] > ND[key]:

                ND[key]=Dict2[key]

        else:

            ND[key]=Dict2[key]

    return ND

print(dict_merge_with_bigger(factory1, factory2))

#第3題

#對python物件不熟(待補)

#第4題

def min_max(array):

    min_arr = np.array([])

    max_arr = np.array([])

    for i in array.transpose():

        min_arr = np.append(min_arr,min(i))

        max_arr = np.append(max_arr,max(i))

    return (arr - min_arr) / (max_arr - min_arr)

import numpy as np

arr = np.array(

[[1,3,5],

 [4,5,6],

 [7,8,9]]

)

min_max(arr)

#第5題

def grouped_mean(df, column_name, threshold):

    dict1 = dict(df[df[column_name]<threshold].mean())

    dict2 = dict(df[df[column_name]>=threshold].mean())

    return (dict1,dict2)

import pandas as pd

data = {"height":[150,170,167,158,160],

        "weight":[38,80,59,60,50],

        "salary":[41, 15, 30, 15, 25]}

df = pd.DataFrame(data)

grouped_mean(df, "weight", 60)