Lagstill/Streamlit_reddit

1import streamlit as st2import pandas as pd3import numpy as np4import matplotlib.pyplot as plt5import seaborn as sns6import praw7import pandas as pd8import datetime as dt9from wordcloud import WordCloud, STOPWORDS10 11reddit = praw.Reddit(client_id='w0cDom4nIf5druip4y9zSw', \12                     client_secret='mtCul8hEucwNky7hLwgkewlLPzH0sg', \13                     user_agent='Profile extractor', \14                     username='CarelessSwordfish541', \15                     password='Testing@2022')16 17st.title('Just Reddit as it is 👀')18 19st.write('This is a simple web app to extract data from Reddit and analyze it.')20 21DATA_URL = 'subreddit_data_v1.csv'22 23 24 25@st.cache26def load_data():27    data = pd.read_csv(DATA_URL)28    lowercase = lambda x: str(x).lower()29    data.rename(lowercase, axis='columns', inplace=True)30    return data31 32data_load_state = st.text('Loading data...')33data = load_data()34data_load_state.text("Done! (using st.cache)")35 36 37if st.checkbox('Show raw data'):38    st.subheader('Raw data')39    st.write(data)40 41subreddit = st.selectbox('Select a subreddit', data['subreddit'].unique())42 43st.subheader('Wordcloud of the most common words in the subreddit')44 45 46comment_words = ''47stopwords = set(STOPWORDS)48 49# iterate through the csv file50for val in data[data['subreddit'] == subreddit]['title']:51    # typecaste each val to string52    val = str(val)53 54    # split the value55    tokens = val.split()56 57    # Converts each token into lowercase58    for i in range(len(tokens)):59        tokens[i] = tokens[i].lower()60 61    comment_words += " ".join(tokens)+" "62 63wordcloud = WordCloud(width = 800, height = 800,64                background_color ='white',65                stopwords = stopwords,66                min_font_size = 10).generate(comment_words)67 68# plot the WordCloud image69plt.figure(figsize = (8, 8), facecolor = None)70 71plt.imshow(wordcloud)72 73plt.axis("off")74 75plt.tight_layout(pad = 0)76st.set_option('deprecation.showPyplotGlobalUse', False)77st.pyplot()78 79 80#Based on the subreddit selected , show the statistics of the subreddit81st.subheader('Statistics of the subreddit')82st.write(data[data['subreddit'] == subreddit].describe())83 84#Based on the subreddit selected display the number of posts per day85st.subheader('Number of posts per day')86st.write(data[data['subreddit'] == subreddit].groupby('created')['title'].count())87 88#Based on the subreddit selected display the number of comments per day89st.subheader('Number of comments per day')90st.write(data[data['subreddit'] == subreddit].groupby('created')['num_comments'].sum())91 92#display a bar chart of the score of the posts93st.subheader('Score of the posts')94st.bar_chart(data[data['subreddit'] == subreddit]['score'])95 96 97 98 99 100# st.subheader('Number of pickups by hour')101# hist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]102# st.bar_chart(hist_values)103 104# # Some number in the range 0-23105# hour_to_filter = st.slider('hour', 0, 23, 17)106# filtered_data = data[data[DATE_COLUMN].dt.hour == hour_to_filter]107 108# st.subheader('Map of all pickups at %s:00' % hour_to_filter)109# st.map(filtered_data)110 111 112