mirror of
https://github.com/aykhans/IMDBDataVisualization.git
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39 lines
1.6 KiB
Python
39 lines
1.6 KiB
Python
import pandas as pd
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import plotly.express as px
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from collections import Counter
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import streamlit as st
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from typing import Optional, List
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class App():
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def __init__(self, page_title: str, page_icon: str, layout: str) -> None:
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self.st = st
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self.st.set_page_config(page_title=page_title, page_icon=page_icon, layout=layout)
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def getDataGenresCount(self, data: pd.DataFrame, genres_type: str) -> Counter:
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if genres_type == 'Movie':
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data = data.query("Title_Type == 'movie' or Title_Type == 'tvMovie'")
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elif genres_type == 'Series':
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data = data.query("Title_Type == 'tvSeries' or Title_Type == 'tvMiniSeries'")
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data_genres = pd.DataFrame({'title': data['Title'], 'genres': data['Genres']})
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genres = []
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for i in data_genres['genres']:
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genres += i.replace(' ', '').split(',')
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genres_count = Counter(genres)
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return genres_count
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def createPieChart(self, data: pd.DataFrame, genres_type: str, selected_genres: List[str]):
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genres_count = self.getDataGenresCount(data, genres_type)
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df = pd.DataFrame({'title': genres_count.keys(), 'count': genres_count.values()}).\
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query('title == @selected_genres')
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pie_chart = px.pie(df, names='title', values='count', title=genres_type + ' genres')
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return pie_chart
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def preprocessingData(self, upload_file: str) -> Optional[pd.DataFrame]:
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if upload_file is not None:
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data = pd.read_csv(upload_file)
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data.rename(columns = {'Title Type': 'Title_Type'}, inplace = True)
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return data
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