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import streamlit as st |
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from gotLibrary import GotLib |
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import plotly.express as px |
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import pandas as pd |
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import matplotlib.pyplot as plt |
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class plot_type: |
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def __init__(self,data): |
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self.data = data |
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self.fig=None |
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self.update_layout=None |
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def bar(self,x,y,color): |
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self.fig=px.bar(self.data,x=x,y=y,color=color) |
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def pie(self,x,y): |
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self.fig = px.pie(self.data,values=x,names=y) |
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def set_title(self,title): |
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self.fig.update_layout( |
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title=f"{title}", |
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yaxis=dict(tickmode="linear"), |
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paper_bgcolor='rgba(0,0,0,0)', |
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plot_bgcolor='rgba(0,0,0,0)', |
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font=dict(color='white',size=18)) |
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def set_title_x(self,title): |
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self.fig.update_layout( |
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title=f"{title}", |
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xaxis=dict(tickmode="linear"), |
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paper_bgcolor='rgba(0,0,0,0)', |
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plot_bgcolor='rgba(0,0,0,0)', |
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font=dict(color='white',size=18)) |
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def set_title_pie(self,title): |
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self.fig.update_layout(title=title, |
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paper_bgcolor='rgba(0,0,0,0)', |
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plot_bgcolor='rgba(0,0,0,0)', |
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font=dict(color='white',size=18)) |
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def plot(self): |
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st.write(self.fig) |
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class slide_bar: |
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value=4 |
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def __init__(self,title,x,y): |
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self.title = title |
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self.x=x |
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self.y=y |
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self.slide_bar = None |
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def set(self): |
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self.slide_bar = st.slider(self.title,self.x,self.y) |
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slide_bar.value=self.slide_bar |
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class select_box: |
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value="tyrion" |
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def __init__(self,data): |
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self.data=data |
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self.box=None |
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def place(self,title,key): |
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header(title) |
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self.box = st.selectbox(str(key),self.data) |
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select_box.value=self.box |
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def title(text,size,color): |
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st.markdown(f'<h1 style="font-weight:bolder;font-size:{size}px;color:{color};text-align:center;">{text}</h1>',unsafe_allow_html=True) |
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def header(text): |
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st.markdown(f"<p style='color:white;'>{text}</p>",unsafe_allow_html=True) |
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@st.cache(persist=True,suppress_st_warning=True) |
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def load_data(): |
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df = pd.read_csv('final_data.csv') |
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df = df.iloc[:,1:] |
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return df |
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df = load_data() |
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got = GotLib(df) |
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with open("styles/style.css") as f: |
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st.markdown(f'<style>{f.read()}</style>',unsafe_allow_html=True) |
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st.markdown('<h1 style="text-align:center;color:white;font-weight:bolder;font-size:100px;">GAME<br>OF<br>THRONES</h1>',unsafe_allow_html=True) |
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st.markdown('<h2 style="text-align:center;color:white;">An analysis..</h2>',unsafe_allow_html=True) |
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st.image('images/got1.jpg',width=700) |
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st.markdown('### This is an analysis based project on the tv series game of thrones') |
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title("Top characters based on number of words spoken in a season",60,"white") |
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header('season') |
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option_1_s = st.selectbox('',[1,2,3,4,5,6,7,8]) |
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header("number of results") |
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num = st.slider("",4,50) |
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temp_data = got.show_top_by_season(option_1_s) |
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number=10 |
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bar1 = plot_type(temp_data[-num:]) |
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bar1.bar("spoken_words","character","spoken_words") |
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bar1.set_title(f"Season {option_1_s}") |
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bar1.plot() |
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title("Overall top characters based on number of spoken words",60,'white') |
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header("number of results") |
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num1 = st.slider("",5,60) |
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temp_data1 = got.get_overall_top() |
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bar2 = plot_type(temp_data1[-num1:]) |
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bar2.bar("words","character","words") |
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bar2.set_title("Overall Top") |
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bar2.plot() |
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title("Character's number of dialogues over the seasons",60,"white") |
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st.markdown('### NOTE: displaying only top 100 characters in drop downs as there are more than 500+ it would be awkward to display it all :)') |
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characters = got.get_data_seasons() |
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stb1 = select_box(characters) |
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stb1.place("character",0) |
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@st.cache(persist=True) |
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def sbyc(df,stb1): |
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return got.show_bar_by_character_allSeason(stb1) |
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t_data = sbyc(df,stb1.value) |
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bar0 = plot_type(t_data) |
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bar0.bar("season","spoken_words","spoken_words") |
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bar0.set_title_x(stb1.value) |
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bar0.plot() |
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title("Percentage of a character's performance in seasons",60,"white") |
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st.write("what is the character's distribution of his/her/(uhh. you know the rest) dialogue percentage over the seasons") |
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stb2 = select_box(characters) |
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stb2.place("character",9) |
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t_data1 = got.cal_importance(df,stb2.value) |
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pie2 = plot_type(t_data1) |
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pie2.pie("imp","season") |
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pie2.set_title_pie(stb2.value) |
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pie2.plot() |
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title('Most number of words spoken by a character',60,'white') |
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st.markdown('#### removing all the stop words in the sense common words.') |
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select_box1 = select_box(characters) |
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select_box1.place('character',1) |
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header("range") |
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num2 = slide_bar("",5,55) |
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num2.set() |
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temp_data2,size = got.get_most_spokenwords_by_character(df,select_box1.value,num2.value) |
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bar3 = plot_type(temp_data2) |
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bar3.bar("frequency","words","frequency") |
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bar3.set_title(f"{select_box1.value.capitalize()} total words spoken - {size}") |
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bar3.plot() |
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title("WordCloud of a character",60,'white') |
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st.markdown('#### It may take a few seconds to load the result, so please hold on to your dragons.') |
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select_box2 = select_box(characters) |
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select_box2.place('character',2) |
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header('range') |
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sl = slide_bar('',50,200) |
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sl.set() |
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@st.cache(persist=True,suppress_st_warning=True) |
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def swc(df,v1,v2): |
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return got.show_word_cloud(df,v1,v2) |
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wc = swc(df,sl.value,select_box2.value) |
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fig = plt.figure(figsize=(8,8)) |
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plt.imshow(wc,interpolation="bilinear") |
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plt.axis('off') |
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plt.title(select_box2.value,fontsize=18) |
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plt.tight_layout() |
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st.pyplot(fig) |
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title("Emotional characteristics",70,"white") |
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st.write("The below pie chart depicts the distribution of emotions of a character.") |
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st.write('Note: This is purely my calculations based on the text-corpus I created and also based on the words used by a character.') |
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select_box3 = select_box(characters) |
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select_box3.place('character',3) |
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temp_data3 = got.cal_character(select_box3.value) |
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pie1 = plot_type(temp_data3['data']) |
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pie1.pie(temp_data3['y'],temp_data3['x']) |
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pie1.set_title_pie(select_box3.value) |
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pie1.plot() |
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title("Most used name by a character",50,"white") |
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stb = select_box(characters[:50]) |
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stb.place("character",4) |
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temp_df = got.most_name(stb.value) |
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num_range = temp_df.shape[0] |
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rangesl = slide_bar("",1,num_range) |
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rangesl.set() |
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bar5 = plot_type(temp_df.iloc[-rangesl.value:,:]) |
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bar5.bar("number","name","number") |
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bar5.set_title(stb.value) |
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bar5.plot() |
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title('Similar Characters',60,'white') |
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st.write('The chart shows characters who are similar to a character with their similarity precentage, based on their similar usage of words, this same alogrithm is also used in movie recommender systems.') |
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st.write('Note: This is very much experimental and purely based on the scripts. And only depends on script text and nothing else.') |
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ch=characters[:] |
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ch1 = select_box(ch) |
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ch1.place('character',5) |
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val=ch1.value |
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results = got.get_similar_character(val) |
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colors = ['rgb(0,255,42)','rgb(221, 235, 30)','rgb(224, 91, 43)'] |
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char = list(results['character']) |
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score = list(results['similarity']) |
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i=0 |
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for name,sc in zip(char,score): |
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st.markdown(f"<h3 style='text-align:center;color:rgb(196, 196, 196);'><span style='font-weight:bolder;color:{colors[i]};font-size:50px;'>{name} </span> [{sc}%]</h3>",unsafe_allow_html=True) |
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i+=1 |
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st.write(' ') |
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st.markdown('#### The dataset here is created from the scripts, involved a lot of data cleaning,wrangling and pre-processing!. Took a lot of time to prepare it!. And is 85% accurate.') |
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st.write('check the box below to peak at the dataset') |
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if st.checkbox('',False): |
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st.subheader("Game_of_Thrones") |
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st.write(df) |
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st.write('') |
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st.write('') |
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st.markdown('<h3 style="text-align:center;">Made By <span style="color:#4f9bce;font-weight:bolder;font-size:40px;">Mario 😎</span></h3>',unsafe_allow_html=True) |
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st.markdown('<h2 style="text-align:center;text-decoration:none;font-weight:bolder;"><a style="text-decoration:none;color:rgb(96, 235, 133);" href="https://github.com/Mario-Vishal">-> GitHub <-</a></h2>',unsafe_allow_html=True) |
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st.markdown('<h2 style="text-align:center;text-decoration:none;font-weight:bolder;"><a style="text-decoration:none;color:rgb(20, 166, 219);" href="https://www.linkedin.com/in/mario-vishal">-> Linkedin <-</a></h2>',unsafe_allow_html=True) |
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st.markdown('<h2 style="text-align:center;text-decoration:none;font-weight:bolder;"><a style="text-decoration:none;color:red;" href="mailto:[email protected]">-> Contact Me <-</a></h2>',unsafe_allow_html=True) |
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