Upload app.py

app.py

@@ -1,15 +1,42 @@
-import streamlit as st
-import datasets
 from datasets import load_dataset
-import pandas as pd 
+import streamlit as st
+import pandas as pd
+import re
+import nltk
+from wordcloud import WordCloud, STOPWORDS
+from nltk.corpus import stopwords
+nltk.download("stopwords")
+stop = stopwords.words('english')
+
+dataset = load_dataset("huggingartists/gorillaz")
+df = pd.DataFrame.from_dict(dataset["train"])
+
+st.dataframe(df)
+st.write("Removed special characters")
 
-def load_data(dataset_name):
-    dataset = load_dataset(dataset_name)
-    return dataset
+def standardize(text, remove_digits=True):
+    text=re.sub('[^a-zA-Z\d\s]', '',text)
+    text = text.lower()
 
+    return text
 
-dataset = load_dataset("fake_news_english")
-df = pd.DataFrame.from_records(dataset)
-st.write("loading dataset")
+df.text = df.text.apply(lambda x: ' '.join([word for word in x.split() if word not in (stop)]))
+df.text=df.text.apply(standardize)
 st.dataframe(df)
-st.write("loaded")
+
+words = df.text.str.split(expand=True).unstack().value_counts()
+st.bar_chart(words[20:40])
+st.set_option('deprecation.showPyplotGlobalUse', False)
+
+import matplotlib.pyplot as plt
+def word_cloud(content, title):
+    wc = WordCloud(background_color='white', max_words=200,
+                  stopwords=STOPWORDS, max_font_size=50)
+    wc.generate(" ".join(content.index.values))
+    fig = plt.figure(figsize=(16, 13))
+    plt.title(title, fontsize=20)
+    plt.imshow(wc.recolor(colormap='Pastel2', random_state=42), alpha=0.98)
+    plt.axis('off')
+    st.pyplot()
+
+word_cloud(words, "Word Cloud")