import os
from collections import Counter
import matplotlib.pyplot as plt

# ------ For processed data ----------
categories_lookup_dict = {}
sales_data_table = []

# ------ data loc ----------
DATA_FILE = "sales_data.csv"
script_dir = os.path.abspath(os.path.dirname(__file__))
data_loc = os.path.join(script_dir, DATA_FILE)

# ------ load data from file ----------
data_vector = []
with open(data_loc, "r") as file:
    lines = file.readlines()
    for line in lines:
        clean_line = line.strip()
        parts = clean_line.split(",")
        data_vector.append(parts)

# ------ get categories ----------
raw_categories = []
for vector in data_vector:
    raw_categories.append(vector[1])
list_of_categories = list(set(raw_categories))

# ------ categories lookup ----------
id = 111
for category in list_of_categories:
    categories_lookup_dict[category] = id
    id += 1

# ------ load sale data table ----------
for vector in data_vector:
    date, make, price = vector[0], vector[1], vector[2]
    sales_data_table.append([date, make, price])

# ------ Count makes sold ----------
makes = [sale[1] for sale in sales_data_table]
make_count = Counter(makes)

# ------ Bar plot makes sold ----------
labels = list(make_count.keys())
values = list(make_count.values())

plt.figure(figsize=(6, 4))
cmap = plt.cm.get_cmap('tab20')
colors = [cmap(i) for i in range(len(labels))]
bars = plt.bar(labels, values, color=colors)

for bar in bars:
    height = bar.get_height()
    plt.annotate(
        f'{int(height)}',
        xy=(bar.get_x() + bar.get_width() / 2, height),
        xytext=(0, 3),
        textcoords="offset points",
        ha='center', va='bottom',
        fontsize=9
    )

plt.xticks(rotation=45, ha='right')
plt.title('Makes Sold Count')
plt.xlabel('Make')
plt.ylabel('Count')
plt.tight_layout()
plt.show()