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Dataset bacteria_list_200 �� :
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b) Family - �� , � ��
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c) Where found - �� , ��
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d) Harmful for humans- ��, �� , �� ("��" �� "��").
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import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv('bacteria_list_200.csv', delimiter=';')
harmful_df = df[df['Harmful to Humans'] == 'Yes']
nonharmful_df = df[df['Harmful to Humans'] == 'No']
count = harmful_df['Harmful to Humans'].count()
noncount = nonharmful_df['Harmful to Humans'].count()
print(count)

x = ['Harmful', 'Nonharmful']
y = [count, noncount]

plt.bar(x, y)
plt.xlabel('���� ��������')
plt.ylabel('���������� �����')
plt.title('��������� ������� � ���������� ��� �������� ��������')


areas_of_interest = ['Intestinal tract', 'Animal intestines', 'Environment, human gut', 'Human mouth & intestine', 'Human body', 'Lungs', 'Skin, nasal passages', 'Human skin, wounds',  'Throat, nasal passages', 'Human oral cavity', 'Human mucous membranes', 'Water, soil, human clinical samples', 'Soil', 'Soil, improperly canned foods', 'Soil, water, skin flora', 'Soil, water', 'Contaminated water', 'Marine environments', 'Thermal springs', 'Animal mucous membranes', 'Freshwater environments', 'Wastewater treatment systems', 'Infected grasses', 'Plants', 'Infected fish', 'Fish', 'Fermented beverages', 'Dairy products', 'Fermented foods, human clinical samples', 'Water, fish', 'Various environments']
filtered_df = df[df['Where Found'].isin(areas_of_interest)]
counts = filtered_df['Where Found'].value_counts()

counts_df = pd.DataFrame(counts).reset_index()
counts_df.columns = ['Area', 'Count']
total = counts_df['Count'].sum()
counts_df['Percent'] = 100 * counts_df['Count'] / total

others_count = df['Where Found'].value_counts().loc[lambda x: x < counts.sum() * 0.05].sum()
counts['Others'] = others_count
#counts.drop(areas_of_interest, inplace=True)

plt.figure(figsize=(12, 12))
plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=140)
plt.title('������������� �������� �� ������� ��������')

plt.show()

filtered2_df = df.filter(like='Family')
counts2 = filtered2_df.value_counts()
print(counts2)

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bacteria_list_200.csv

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