A rough plotting of Shark Tank investors decisions regarding pitches

Data_sorting.py

with open('season.txt', 'r', encoding="utf8") as f:
    data = f.read()

investments = {}

for pitch in data.split('$'):  # Split all pitches into chunks
    lines = list(pitch.splitlines())  # Split a pitch by lines
    if lines[0]=='': # If the first line is a blank then remove it
        lines.pop(0)
    pitch_number = int(lines[0]) * 10 + int(lines[1]) #The first line and the second line are the two digits of the pitch ID

    price, percentage = (lines[3].split(',')) # The fourth line has the price and percentage presented by the pitch
    investments[pitch_number] = [[int(price), float(percentage)]]  # Add all that info to the investment dict
    if 'none' not in pitch:  # Successful pitches go here to add their investing data to the investment dict
        for line in lines[4:]:  # For lines of (price, percentage, investor) which are the last lines except the final
            price, percentage, name = line.split(',')  # Take out their values
            investments[pitch_number].append([int(price), float(percentage), name])  # put them in a tuple inside the dict





#TODO: Change the function dict to list to dict to array using numpy

Functions.py

import numpy as np
import Data_sorting

def combiner(*args):
    """Takes in a number of tuples of (price, percentage, investor) and combines them into one tuple"""
    price, percentage = 0, 0
    for list in args:
        for element in list:
            price += int(element[0])
            percentage += float(element[1])
    return price, percentage


def investments_to_list(dict, combining=False):
    #Declaring the list used
    failed = [[], []]   # This is for pitches that gone nowhere
    pitch = [[], []]    # This is for pitches that lead to investments
    combined = [[], []] # This is for a combined look at the investments

    #Declaring numpy arrays used
    numpinvestors = np.zeros((6,2,len(dict.keys()))) # Secret trials are here
    count = np.array([0, 0, 0, 0, 0])
    count = 0

    #
    for list in dict.values(): # For every pitch in the dict, failed or successful
        if len(list) > 1: # If its a successful pitch (at least another list or a price, percentage by investor) then go here
            if combining: # When you want a list with the investments of each investor combined into one [price, percentage]
                pitch[0].append((list[0])[0])
                pitch[1].append((list[0])[1])
                price, percentage = combiner(list[1:])
                combined[0].append(price)
                combined[1].append(percentage)

            # The proposed pitch price, percentage goes into this list
            pitch[0].append((list[0])[0])
            pitch[1].append((list[0])[1])

            # Now we deal with price, percentage of
            for i in list[1:]: # Bad Coder! dont ever do what I just did with all these if statements
                # For every investor add the price, percentage to the 1st row, 1st and 2nd column, and [count] layers (3d axis)
                if 'Othaim' in i[2]:
                    numpinvestors[0,:,count] = i[:2]

                elif 'Zamel' in i[2]:
                    numpinvestors[1,:,count] = i[:2]

                elif 'Taiba' in i[2]:
                    numpinvestors[2,:,count] = i[:2]

                elif 'Qahtani' in i[2]:
                    numpinvestors[3, :, count] = i[:2]

                elif 'Kurdi' in i[2]:
                    numpinvestors[4, :, count] = i[:2]

                elif 'Batrjy' in i[2]:
                    numpinvestors[5, :, count] = i[:2]

            count += 1
        else:
            pass
            failed[0].append((list[0])[0])
            failed[1].append((list[0])[1])
    return failed, pitch, combined, numpinvestors

failed, pitch, combined, numpinvestors = investments_to_list(Data_sorting.investments, combining=True)

Main.py

import Data_sorting
import Functions as funcs
import matplotlib.pyplot as plt
import numpy as np

# Importing the Data
failed, pitch, combined, numpinvestors = funcs.investments_to_list(Data_sorting.investments, combining=True)
"""Failed -> pitch went nowhere, Pitch -> pitch lead to an accepted deal, investor -> accepted deals """

# Creating the figure and the axes
fig, ax = plt.subplots(3)


# Plotting the first two axes
ax[0].scatter(failed[0], failed[1], c='red', edgecolors='black', label='Failed Pitches', alpha=0.5, s=200)
ax[1].scatter(pitch[0], pitch[1], c='blue', edgecolors='black', alpha=0.5, label='Successful Pitches', s=200)
ax[1].scatter(combined[0], combined[1], c='green', edgecolors='black', alpha=0.5, label='Accepted Pitches', s=200)


# Plotting the third axe
color = ['y', 'm', 'c', 'k', 'g', 's']
names = ['Othaim', 'Zamel', 'Taiba', 'Qahtani', 'Kurdi', 'Batrjy']
for cnt, investor in enumerate(range(5), 0):
    ax[2].scatter(numpinvestors[cnt,0,:], numpinvestors[cnt,1,:], c=color[cnt], edgecolors='black', alpha=0.5, label=names[cnt], s=200)
ax[2].scatter(0, 0, c='w', edgecolors='w', s=1000)



# Additional Artists
ax[0].legend()
ax[1].legend()
ax[2].legend()
ax[0].set(ylim=[0, 1], xlabel='Riyal', ylabel='Percentage of Company', xlim=[-10e3, 10e5+10e3])
ax[1].set(ylim=[0, 1], xlabel='Riyal', ylabel='Percentage of Company', xlim=[-10e3, 10e5+10e3])
ax[2].set(ylim=[0, 1], xlabel='Riyal', ylabel='Percentage of Company', xlim=[-10e3, 10e5+10e3])



# Showing
plt.show()

season.txt

1
1
سهيل عبدالعزيز, شطافك في جيبك
300000, 0.1
300000, 0.2, Othaim
300000, 0.2, Kurdi
$
1
2
محمد بن مرشد, انحف وانت نايم
500000, 0.5
none
$
1
3
مناهل صابر, مؤسسة مناهل صابر للحلويات
250000, 0.15
none
$
1
4
اسماعيل عبدالقادر, ورشة دوت كوم
360000, 0.2
360000, 0.4, Othaim
$
2
1
رضا عمده, معمل مجوهرات
600000, 0.15
600000, 0.22, Zamel
$
2
2
اكرم الكنيزي, صناعة الالعاب الإلكترونية
400000, 0.3
none
$
2
3
تهاني طلال, مركز صيانة الجوالات
100000, 0.35
none
$
2
4
عبدالهادي الدالي, بنك المهندسين
1000000, 0.15
none
$
2
5
عبدالله السقاف, مطعم فول
900000, 0.2
none
$
2
6
ثامر الزقم, تطبيق هبه
50000, 0.15
none
$
3
1
سامي اوليه, العاب جماعيه
2000000, 0.2
none
$
3
2
طلال فطاني, عربتك
700000, 0.2
400000, 0.2, Batrjy
400000, 0.2, Othaim
$
3
3
خالد عطيه, استخراج السكر من التمر
7500000, 0.5
none
$
3
4
فيصل عشور, تاكو لاكو
200000, 0.15
200000, 0.23, Batrjy
200000, 0.23, Othaim
$
3
5
طلال عبدالله, نطبيق وقت الخدمة
600000, 0.07
none
$
3
6
هند العصيمي, ايرون أكس
300000, 0.1
300000, 0.25, Taiba
$
4
1
عبدالمجيد بامنيف, تطبيق صوتك
300000, 0.1
100000, 0.15, Othaim
100000, 0.15, Kurdi
100000, 0.15, Taiba
$
4
2
عبدالله القرشي, مطعم اكلات آسيوية
600000, 0.3
none
$
4
3
عائشة الدغيلبي, إعادة هوية السجين
500000, 0.51
none
$
4
4
احمد الحربي, تطبيق شحنه
400000, 0.1
none
$
4
5
احلام خوندنة, مصنع الاوراق المضيئة
1600000, 0.7
none
$
5
1
منصور الزهراني, تطبيق عزيز السفر
350000, 0.25
150000, 0.245, Batrjy 
150000, 0.245, Qahtani
$
5
2
علي الخالدي, تحويل الاطعمة
150000, 0.15
none
$
5
3
فهد الحارثي, روح جروب
1500000, 0.49
none
$
5
4
مشعل العوهلي, عربية ورد
250000, 0.4
none
$
5
5
صلاح اكرامي, مركز عناية السيارات
540000, 0.3
none
$
6
1
عبدالله باشير, قهوة قطرات
300000, 0.16
none
$
6
2
سعود الفارس, تطبيق قلم
200000, 0.2
none
$
6
3
منيرة بن عيسى, حزام امان
300000, 0.3
none
$
6
4
محمد طيار, كليب اون اب
200000, 0.15
75000, 0.1, Othaim
75000, 0.1, Kurdi
75000, 0.1, Taiba
75000, 0.1, Qahtani
$
7
1
نواف ابارهيم, سوارة
150000, 0.15
175000, 0.2, Othaim
175000, 0.2, Taiba
$
7
2
محمد المشيقح, بين لينز
500000, 0.2
none
$
7
3
نجلا عبدالمجيد, دانتيلا
50000, 0.1
none
$
7
4
ضحى الجهني, فندق اطفال
1500000, 0.15
none
$
7
5
نبيل الغامدي, شاورما شاطر
2000000, 0.1
none