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import pandas as pd | |
import seaborn as sns | |
import matplotlib.pyplot as plt | |
from wordcloud import WordCloud | |
# Load the dataset internally within the EDA module | |
df = pd.read_csv('Danamon Mobile Banking Reviews(D-Bank Pro).csv') | |
def visualize_wordcloud(): | |
"""Generate a word cloud for the 'content' column.""" | |
wordcloud = WordCloud(width=800, height=400, background_color='white').generate(' '.join(df['content'])) | |
plt.figure(figsize=(10, 7)) | |
plt.imshow(wordcloud, interpolation='bilinear') | |
plt.axis('off') | |
plt.title('Word Cloud for Reviews') | |
return plt.gcf() # Return the current figure | |
def plot_review_lengths(): | |
"""Plot the distribution of review lengths.""" | |
review_lengths = df['content'].str.len() | |
plt.figure(figsize=(12, 6)) | |
sns.histplot(review_lengths, bins=50, kde=True) | |
plt.title('Distribution of Review Lengths') | |
plt.xlabel('Review Length (characters)') | |
plt.ylabel('Number of Reviews') | |
return plt.gcf() # Return the current figure | |
def rating_distribution(): | |
"""Plot the distribution of ratings.""" | |
ratings = df['score'].value_counts() | |
plt.figure(figsize=(10, 6)) | |
sns.barplot(x=ratings.index, y=ratings.values, palette="viridis") | |
plt.title('Rating Distribution') | |
plt.xlabel('Rating') | |
plt.ylabel('Number of Reviews') | |
return plt.gcf() # Return the current figure | |