add docker and py file

Dockerfile

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+# read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
+FROM python:3.9
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . .
+
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]

main.py

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+from logging import log
+from dash import Dash, html, dcc, callback, Output, Input
+import pandas as pd
+import plotly.express as px
+from plotly.graph_objs import scatter
+import plotly.graph_objects as go
+df = pd.read_csv('1711709179672.csv',na_values="None")
+
+df.insert(4,"Size",(10 * df["Amount"].abs())/100)
+
+df['Departments'].fillna("no departments",inplace=True)
+
+
+
+
+app = Dash(__name__)
+
+
+app.layout = html.Div(children = [
+    html.Div(
+            className="row",
+            children=[
+                html.Div(
+                    className="four columns div-user-controls",
+                    children=[
+                        html.H2("XPENCE-INSIGHT"),
+                        html.H3("""Visualising Xpence transaction"""),
+                        html.H4("""Pick one User from the dropdown below."""),
+                    ],
+                ),
+                html.Div(
+                    
+                    className="eight columns div-for-charts bg-grey",
+                    
+                    children=[
+            dcc.Dropdown(
+                df['Card holder'].unique(),
+                'Radu Pertescu',
+                id='xaxis-column',
+                placeholder= "Radu Pertescu",
+               
+            ),
+            dcc.Graph(id="scatterGraph",animate=True),
+            dcc.Graph(id='barGraph'),
+            dcc.Graph(id='areaGraph'),
+            dcc.Graph(id='histogramGraph')
+                    ]
+                ),
+            ]
+    ),
+    
+    #dcc.Graph(figure=px.scatter(df,x="Transaction Date", y="Amount")),
+    
+    ##dcc.Graph(figure=px.funnel(df,x='Amount',y='Category'))
+    #dcc.Graph(figure=px.scatter(df,x="Amount", y="Transaction Date",color="Card holder")),
+    # dcc.Graph(figure=px.icicle(df,path=[px.Constant("all"), 'Approval Status', 'Card holder','Category'],color='Category',color_continuous_scale='RdBu')),
+    
+    # dcc.Graph(figure=px.sunburst(df,path=["Transaction Type","Card holder","Approval Status"],color='Amount')),
+    # dcc.Graph(figure=px.parallel_categories(df,dimensions=["Card holder","Category","Branches","Departments","Approval Status","Receipt"],color="Amount")),
+    # dcc.Graph(figure=px.scatter(df,x="Amount", y="Merchant",color="Card holder",opacity=0.7)),
+
+   
+
+])
+
+
+@callback(
+    Output("scatterGraph","figure"),
+    Input("xaxis-column","value")
+    
+)
+def update_graph(userName):
+    filtered_df = df[df["Card holder"] == userName]
+    fig = px.scatter(filtered_df,x="Amount", y="Transaction Date",color="Transaction Type",title="Transaction type and amount based on date")
+    
+    return fig
+
+
+@callback(
+    Output("barGraph","figure"),
+    Input("xaxis-column","value")
+)
+def update_bar_graph(userName):
+    filtered_df = df[df["Card holder"] == userName]
+    count_data_frame = filtered_df
+    count_data_frame = filtered_df.groupby('Category').count().reset_index()
+    fig = px.bar(count_data_frame,x="Category", y="Amount",color='Category',title="Category count")
+    return fig
+
+@callback(
+    Output("areaGraph","figure"),
+    Input("xaxis-column","value")
+)
+def update_area_graph(userName):
+    filtered_df = df[df["Card holder"] == userName]
+    filtered_df['Transaction Date'] = pd.to_datetime(filtered_df['Transaction Date'],format='%d/%m/%Y %H:%M')
+    filtered_df['Transaction Date'] = filtered_df['Transaction Date'].dt.round('D')
+    filtered_df['Transaction Date'].dt.strftime("%Y-%m-%d")
+    transaction_data_frame = filtered_df
+    transaction_data_frame = filtered_df.groupby('Transaction Date').count().reset_index()
+    fig = px.area(transaction_data_frame,x='Transaction Date',y='Amount',markers=True,title="Number of transaction on a single day")
+    return fig
+
+
+@callback(
+    Output("histogramGraph","figure"),
+    Input("xaxis-column","value")
+)
+def update_histogram_graph(userName):
+    filtered_df = df[df["Card holder"] == userName]
+    fig=px.histogram(filtered_df,x='Approval Status',color="Approval Status",title="Approval status count")
+    return fig
+
+
+if __name__ == '__main__':
+    app.run(port='8051',debug=True)