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import streamlit as st | |
import seaborn as sns | |
sns.set() | |
import pandas as pd | |
import numpy as np | |
import matplotlib.pyplot as plt | |
from PIL import Image | |
image = Image.open('barchart_hour.jpg') | |
def run(): | |
# Membuat Title | |
st.title('Exploratory Data Analysis') | |
# Membuat Sub Header | |
st.subheader('EDA For American Youtube trending videos') | |
# Membuat Deskripsi | |
st.write('This page made by Sam') | |
# Membuat Garis lurus | |
st.markdown('---') | |
# Magic Syntax | |
''' | |
Ma ma mia ma ma mia | |
''' | |
# Show DataFrame | |
raw_data = pd.read_csv('USvideos.csv') | |
st.dataframe(raw_data.sample(100)) | |
st.write('### scatterplot views(in hundred millions) vs likes') | |
fig = plt.figure(figsize=(15, 10)) | |
sns.scatterplot(x=raw_data['views'],y=raw_data['likes']) | |
st.pyplot(fig) | |
st.write('### scatterplot views(in hundred millions) vs comment_counts') | |
fig = plt.figure(figsize=(15, 10)) | |
sns.scatterplot(x=raw_data['views'],y=raw_data['comment_count'], palette='hls') | |
st.pyplot(fig) | |
st.write('### Views(in millions) by video published hour') | |
st.image(image, caption=None, width=None, use_column_width=None, clamp=False, channels="RGB", output_format="auto") | |
if __name__ == '__main__': | |
run() |