gary136

gary136

import pandas as pd
import requests
import numpy as np
from io import StringIO
import time
import matplotlib.pyplot as plt
import html5lib
from datetime import datetime, timedelta
import calendar
import datetime as dt

gary136

SELECT * FROM
(
    上市公司財務比率 (FROM 損益表) 
    UNION 
    上櫃公司財務比率 (FROM 損益表)
) A
JOIN
(
    上市公司財務比率 (FROM 資產負債表 / 現金流量表) 
    UNION 

gary136

def add_key(x):
    sku = x[0]
    r_id = x[1]
    for ele in sku:
        ele['receipt_id'] = r_id
    return sku
df['sku'] = df[['sku', 'receipt_id']].apply(add_key, axis=1)

gary136

import time
import numpy as np
import requests
import pandas as pd

# prepare
url = 'https://raw.githubusercontent.com/hermitdave/FrequencyWords/master/content/2016/en/en_50k.txt'
r = requests.get(url)
d = r.text.split('\n')[:-1]
word = [t[0] if len(t)==2 else None for t in [i.split(' ') for i in d]]

gary136

gary136

def func(xlist):
    return 2*(xlist[0]-2.3)**2+3*(xlist[0]-4.1)*(xlist[1]-6.5)+5*(xlist[1]-8.0)**2

# functions
def partial_derivative(f, x_list, odr, epsilon = 1e-6, **kargs):
    h_list = x_list.copy()
    
    h_list[odr] = x_list[odr] + epsilon
    fx = f(x_list, **kargs)
    fh = f(h_list, **kargs)

gary136

def test(xlist):
    # xlist is the list of the variables we have, and in this particular instance we have two variables     
    return 2*xlist[0]**2+3*xlist[0]*xlist[1]+5*xlist[1]**2

# functions
def partial_derivative(f, x_list, odr, epsilon = 1e-6, **kargs):
    # 此為模擬偏微分會有少量誤差
    h_list = x_list.copy()
    
    h_list[odr] = x_list[odr] + epsilon

gary136

def vocabulary(sample, start, end):
    import string
    p = sample.replace('-', ' ').translate(str.maketrans('', '', string.punctuation)).split()
    p = [i.lower() for i in p]
    p = [(i, df[df.word==i].index[0], list(df[df.word==i]['dic'])[0]) \
         if i in np.array(df.word) else (i, 99999, 'N') for i in p]
    w = np.array(list(set(p)))[:,0]
    r = np.array(list(set(p)))[:,1].astype(int)
    d = np.array(list(set(p)))[:,2]
    d = pd.DataFrame({'word':w

gary136