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import streamlit as st
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import plotly.express as px
from PIL import Image
def run() :
# Membuat Title
st.markdown("<h1 style='text-align: center;'>Exploratory Data Analysis</h1>", unsafe_allow_html=True)
st.write('Berikut adalah EDA dan Workcloud dari Setiap Kategori Tweet')
# Import DF
df_eda = pd.read_csv('eda_preprocessing.csv')
# Membuat Sub Header
st.subheader('**Persebaran Kategori Tweet**')
# Membuat visualisasi Distribusi Tweet
fig, ax =plt.subplots(1,2,figsize=(15,6))
sns.countplot(x='cyberbullying_type', data=df_eda, palette="winter", ax=ax[0])
ax[0].set_xlabel("cyberbullying_type", fontsize= 12)
ax[0].set_ylabel("# of Tweet", fontsize= 12)
fig.suptitle('Tweet Type Distribution', fontsize=18, fontweight='bold')
ax[0].set_ylim(0,10000)
ax[0].tick_params(axis='x', rotation=90)
plt.xlabel("cyberbullying_type", fontsize= 12)
plt.ylabel("# of Tweet", fontsize= 12)
for p in ax[0].patches:
ax[0].annotate("%.0f"%(p.get_height()), (p.get_x() + p.get_width() / 2,
p.get_height()+205), ha='center', va='center',fontsize = 11)
df_eda['cyberbullying_type'].value_counts().plot(kind='pie',autopct='%1.1f%%', textprops = {"fontsize":12})
ax[1].set_ylabel("% of Tweet", fontsize= 12)
st.pyplot(fig)
# Membuat Sub Header
st.subheader('**All Tweet**')
st.image('https://imgur.com/quc6ru7.png')
# Membuat Sub Header
st.subheader('**Age Tweet**')
st.image('https://imgur.com/WB2tdlJ.png')
# Membuat Sub Header
st.subheader('**Gender Tweet**')
st.image('https://imgur.com/Pd9G2k9.png')
# Membuat Sub Header
st.subheader('**Religion Tweet**')
st.image('https://imgur.com/GE8Sj39.png')
# Membuat Sub Header
st.subheader('**Other Cyberbullying Tweet**')
st.image('https://imgur.com/sr6MYGO.png')
# Membuat Sub Header
st.subheader('**Not Cyberbullying Tweet**')
st.image('https://imgur.com/iWyNSVH.png')
if __name__ == '__main__':
run()