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Merge pull request #892 from PRIYANSHU2026/f146
here is my EA stocks app
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Financial APIs/EA (Electronic Arts) Stocks app/ EDA app.py
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import pandas as pd | ||
import matplotlib.pyplot as plt | ||
import gradio as gr | ||
import os | ||
import numpy as np | ||
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# Define the path to the CSV file | ||
csv_file_path = 'EA.csv' | ||
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def visualize_eda(start_date, end_date): | ||
# Create a directory to save plots | ||
if not os.path.exists('eda_plots'): | ||
os.makedirs('eda_plots') | ||
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# Initialize output paths | ||
line_plot_path = 'eda_plots/line_plot.png' | ||
bar_plot_path = 'eda_plots/bar_plot.png' | ||
hist_plot_path = 'eda_plots/hist_plot.png' | ||
scatter_plot_path = 'eda_plots/scatter_plot.png' | ||
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# Load the data from the CSV file | ||
try: | ||
df = pd.read_csv(csv_file_path, parse_dates=True, index_col=0) | ||
except Exception as e: | ||
return [None, None, None, None, f"Error loading CSV file: {e}"] | ||
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# Filter the data by the given date range | ||
try: | ||
df = df.loc[start_date:end_date] | ||
except Exception as e: | ||
return [None, None, None, None, f"Error filtering data: {e}"] | ||
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# Check for and handle non-numeric columns | ||
df_numeric = df.select_dtypes(include=['float64', 'int64']) | ||
if df_numeric.empty: | ||
return [None, None, None, None, "Error: No numeric data found in CSV file."] | ||
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# Plot 1: Line plot of all numerical features | ||
try: | ||
plt.figure(figsize=(12, 6)) | ||
for column in df_numeric.columns: | ||
plt.plot(df_numeric.index, df_numeric[column], label=column) | ||
plt.title('Line Plot of Numerical Features') | ||
plt.xlabel('Date') | ||
plt.ylabel('Value') | ||
plt.legend() | ||
plt.savefig(line_plot_path) | ||
plt.close() | ||
except Exception as e: | ||
return [None, None, None, None, f"Error generating line plot: {e}"] | ||
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# Plot 2: Bar plot of average values per month | ||
try: | ||
plt.figure(figsize=(12, 6)) | ||
monthly_avg = df_numeric.resample('M').mean() | ||
monthly_avg.plot(kind='bar', figsize=(15, 7)) | ||
plt.title('Monthly Average of Numerical Features') | ||
plt.xlabel('Month') | ||
plt.ylabel('Average Value') | ||
plt.savefig(bar_plot_path) | ||
plt.close() | ||
except Exception as e: | ||
return [None, None, None, None, f"Error generating bar plot: {e}"] | ||
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# Plot 3: Histogram of numerical features | ||
try: | ||
plt.figure(figsize=(12, 6)) | ||
df_numeric.hist(bins=30, figsize=(15, 7)) | ||
plt.suptitle('Histogram of Numerical Features') | ||
plt.savefig(hist_plot_path) | ||
plt.close() | ||
except Exception as e: | ||
return [None, None, None, None, f"Error generating histogram: {e}"] | ||
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# Plot 4: Scatter plot matrix of numerical features | ||
try: | ||
from pandas.plotting import scatter_matrix | ||
plt.figure(figsize=(12, 12)) | ||
scatter_matrix(df_numeric, alpha=0.2, figsize=(15, 15), diagonal='kde') | ||
plt.suptitle('Scatter Plot Matrix of Numerical Features') | ||
plt.savefig(scatter_plot_path) | ||
plt.close() | ||
except Exception as e: | ||
return [None, None, None, None, f"Error generating scatter plot matrix: {e}"] | ||
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# Return paths to generated plots | ||
return [line_plot_path, bar_plot_path, hist_plot_path, scatter_plot_path, None] | ||
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# Define the Gradio interface | ||
iface = gr.Interface( | ||
fn=visualize_eda, | ||
inputs=[ | ||
gr.Textbox(label="Start Date (YYYY-MM-DD)", value="2002-01-02"), | ||
gr.Textbox(label="End Date (YYYY-MM-DD)", value="2022-10-10") | ||
], | ||
outputs=[ | ||
gr.Image(type="filepath", label="Line Plot"), | ||
gr.Image(type="filepath", label="Bar Plot"), | ||
gr.Image(type="filepath", label="Histogram"), | ||
gr.Image(type="filepath", label="Scatter Plot Matrix"), | ||
gr.Textbox(label="Error Message", type="text") # Add a textbox for error messages | ||
], | ||
live=False # This will add an explicit "Submit" button | ||
) | ||
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# Launch the Gradio app | ||
iface.launch(share=True, inbrowser=True) |
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