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import gradio as gr
import os
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
def dataset_change(dataset):
df = pd.read_csv(dataset.name)
features = df.columns
features_object_list = [feature for feature in features]
describe = df.describe(include='all')
print(describe)
return describe.reset_index(), gr.Dropdown.update(choices = features_object_list), gr.Dropdown.update(choices = features_object_list)
def feature_select(dataset, feature, hue = None):
df = pd.read_csv(dataset.name)
non_numeric_cols = df.select_dtypes('object').columns.tolist()
if feature in non_numeric_cols:
kde = False
plot2 = plt.figure()
if hue:
sns.countplot(x = feature, data = df, palette='rainbow', hue = hue)
else:
sns.countplot(x = feature, data = df, palette='rainbow')
else:
kde = True
plot2 = plt.figure()
if hue:
sns.boxplot(x = feature, data = df, hue = hue)
else:
sns.boxplot(x = feature, data = df )
plot1 = plt.figure()
if hue:
sns.histplot(data = df, x = feature, kde = kde, hue = hue, multiple="stack")
else:
sns.histplot(data = df, x = feature, kde = kde)
return plot1, plot2
with gr.Blocks() as demo:
gr.Markdown("""## Input Dataset""")
with gr.Row():
dataset = gr.File()
with gr.Row():
dataframe = gr.Dataframe()
gr.Markdown("""## Select the feature to visualize""")
with gr.Row():
with gr.Column():
features = gr.Dropdown(label="Select feature to visualize")
with gr.Column():
hue = gr.Dropdown(label="Select hue")
with gr.Row():
btn = gr.Button("Visualize")
gr.Markdown("""## Visualization""")
with gr.Row():
plot1 = gr.Plot()
with gr.Row():
plot2 = gr.Plot()
gr.Examples(
examples=[],
fn = dataset_change,
inputs = dataset,
outputs = [dataframe, features, hue]
)
dataset.change(fn=dataset_change,
inputs = dataset,
outputs = [dataframe, features, hue]
)
btn.click(fn=feature_select,
inputs=[dataset, features, hue],
outputs=[plot1, plot2]
)
demo.launch(debug=True) |