diff --git a/dashboard with outputs b/dashboard with outputs
new file mode 100644
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+++ b/dashboard with outputs	
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+import dash
+import plotly.express as px
+import pandas as pd
+
+# Data Exploration with Pandas (python)
+# -----------------------------------------------------------------
+
+df = pd.read_csv("reviews.csv")
+
+print(df[:5])
+print(df.iloc[:5, [2,3,5,10]])
+print(df.Genre.nunique())
+print(df.Genre.unique())
+print(sorted(df.Year.unique()))
+
+# Data Visualization (Python)
+# -----------------------------------------------------------------
+
+fig_pie = px.pie(data_frame=df, names='Genre', values='a') // 
+fig_pie = px.pie(data_frame=df, names='Genre', values='b') // 
+fig_pie.show()
+
+fig_bar = px.bar(data_frame=df, x='Genre', y='a')
+fig_bar.show()
+
+fig_hist = px.histogram(data_frame=df, x='Year', y='a')
+fig_hist.show()
+
+# Interactive Graphs with Dash
+# -----------------------------------------------------------------
+
+import dash_core_components as dcc
+import dash_html_components as html
+from dash.dependencies import Output, Input
+
+app = dash.Dash(__name__)
+
+app.layout=html.Div([
+    html.H1("Graph Analysis with Charming Data"),
+    dcc.Dropdown(id='genre-choice',
+                 options=[{'label':x, 'value':x}
+                          for x in sorted(df.Genre.unique())],
+                 value='Action'
+                 ),
+    dcc.Graph(id='my-graph',
+              figure={}),
+])
+@app.callback(
+    Output(component_id='my-graph', component_property='figure'),
+    Input(component_id='genre-choice', component_property='value')
+)
+def interactive_graphs(value_genre):
+    print(value_genre)
+    dff = df[df.Genre==value_genre]
+    fig = px.bar(data_frame=dff, x='Year', y='Japan Sales')
+    return fig
+
+
+if __name__=='__main__':
+    app.run_server()