I want to upload any csv and have a dropdown menu that populates the column names as the options.
The size of the dropdown menu is changing everytime I upload a csv so something is getting passed to it, but it won’t display any of the options. Am I doing something wrong or is this a bug?
Any help is much appreciated!
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div([
html.H1("Model Builder", style={'text-align': 'center'}),
dcc.Upload(
id='datatable-upload',
children=html.Div([
'Drag and Drop or ',
html.A('Select Files')
]),
style={
'width': '100%', 'height': '60px', 'lineHeight': '60px',
'borderWidth': '1px', 'borderStyle': 'dashed',
'borderRadius': '5px', 'textAlign': 'center', 'margin': '10px'
},
),
html.Br(),
html.H5("Sample Data", style={'text-align': 'center'}),
html.Br(),
dash_table.DataTable(id='datatable-upload-container'),
html.Br(),
html.H5("Summary Statistics", style={'text-align': 'center'}),
html.Br(),
dash_table.DataTable(id='summary_stats'),
html.Br(),
html.H5("Data Types", style={'text-align': 'center'}),
html.Br(),
dash_table.DataTable(id='data-types'),
html.Br(),
html.H5("Graph Me", style={'text-align': 'center'}),
html.Br(),
dcc.Dropdown(id="variables"),
html.Br(),
dcc.Graph(id='datatable-upload-graph')
])
def parse_contents(contents, filename):
content_type, content_string = contents.split(',')
decoded = base64.b64decode(content_string)
if 'csv' in filename:
# Assume that the user uploaded a CSV file
return pd.read_csv(
io.StringIO(decoded.decode('utf-8')))
elif 'xls' in filename:
# Assume that the user uploaded an excel file
return pd.read_excel(io.BytesIO(decoded))
#---------------------------------------------------------------------------------------------
# Sample data
@app.callback(Output('datatable-upload-container', 'data'),
Output('datatable-upload-container', 'columns'),
Input('datatable-upload', 'contents'),
State('datatable-upload', 'filename'))
def update_output(contents, filename):
if contents is None:
return [{}], []
df = parse_contents(contents, filename)
return df.head().to_dict('records'), [{"name": i, "id": i} for i in df.columns]
#----------------------------------------------------------------------------------------------
#Summary stats
@app.callback(Output('summary_stats', 'data'),
Output('summary_stats', 'columns'),
Input('datatable-upload', 'contents'),
State('datatable-upload', 'filename'))
def update_output(contents, filename):
if contents is None:
return [{}], []
df = parse_contents(contents, filename)
dff = df.describe().round(2).transpose()
dff.reset_index(inplace = True)
datatypes = df.dtypes
print(datatypes)
dff['dataType'] = datatypes
return dff.to_dict('records'), [{"name": i, "id": i} for i in dff.columns]
#----------------------------------------------------------------------------------------------
#Data type
@app.callback(Output('data-types', 'data'),
Output('data-types', 'columns'),
Input('datatable-upload', 'contents'),
State('datatable-upload', 'filename'))
def update_output(contents, filename):
if contents is None:
return [{}], []
df = parse_contents(contents, filename)
dff = df.dtypes
return dff.to_json(), [{"name": i, "id": i} for i in dff.columns]
#----------------------------------------------------------------------------------------------
#Dropdown to select histogram variable - options won't display but they appear to populate
@app.callback(Output('variables', 'options'),
Input('datatable-upload', 'contents'),
State('datatable-upload', 'filename'))
def update_output(contents, filename):
if contents is None:
return [{}], []
df = parse_contents(contents, filename)
cols = [{"name": i, "id": i} for i in df.columns]
print(cols)
type(cols)
return cols
#----------------------------------------------------------------------------------------------
#histogram - not connected
@app.callback(Output('datatable-upload-graph', 'figure'),
Input('datatable-upload-container', 'data'))
def display_graph(rows):
df = pd.DataFrame(rows)
if (df.empty or len(df.columns) < 1):
return {
'data': [{
'x': [],
'y': [],
'type': 'bar'
}]
}
return {
'data': [{
'x': df[df.columns[0]],
'y': df[df.columns[1]],
'type': 'bar'
}]
}
#----------------------------------------------------------------------------------------------
if __name__ == '__main__':
app.run_server(debug=False)
