Issue:
I'm trying to load a simple plotly scatter plot, where
- x axis = keyword
- y axis = date
- color = locale
however, even plotly throws a key error every time I add the "color" variable. The error code I get states that I don't have a column by that name, but when I print the column names I see the column there.
Anyone faced a similar issue?
Data:
Code:
# Importing needed libraries
import dash
import dash_core_components as dcc
import dash_html_components as html
import dash_bootstrap_components as dbc
import dash_table
from dash.dependencies import Input, Output
import plotly.express as px
import pandas as pd
import random
import datetime
import plotly.graph_objects as go
# Reading the dataframe
df = pd.read_csv('./beanstalk_app/ti_data_ti_dash_v1.csv')
categories = df['category']
locales = df['locale']
# clean dataframe
ti_data = df.copy()
ti_data = ti_data.sample(1000)
# Contents of the app
# 1.Controls
# 1.1 Dropdown list
locs = dcc.Dropdown(id='choose_loc',
options=[
{
'label': locale, 'value': locale
} for locale in locales.unique()
],
placeholder='Select Locale')
cats = dcc.Dropdown(id='choose_cat',
options=[
{
'label': c, 'value': c
} for c in categories.unique()
],
placeholder='Select Category')
# 1.2 DatePicker
datepick = dcc.DatePickerRange(
id='choose_date',
min_date_allowed=df.date.min(),
max_date_allowed=df.date.max(),
initial_visible_month=df.date.min(),
clearable=True,
start_date=df.date.min(),
end_date=df.date.max()
)
# 2.Interactive table
table = dash_table.DataTable(
id='datatable',
columns=[
{"name": i, "id": i, "selectable": True, "presentation": "markdown"}
if i == "google_query"
else {"name": i, "id": i, "selectable": True}
for i in df.columns
],
data=df.to_dict('records'),
editable=False,
filter_action="native",
sort_action="native",
sort_mode="multi",
column_selectable="single",
row_selectable="multi",
row_deletable=True,
selected_columns=[],
selected_rows=[],
page_action="native",
page_current=0,
page_size=10,
style_cell={
'whiteSpace': 'normal',
'height': 'auto',
},
)
# Initialize the app
app = dash.Dash(__name__)
app.title = 'Dot Graph Demo - All Entities'
app.layout = html.Div([
# modifiable table
dbc.Container([
dbc.Row(
[
dbc.Col(locs, width=4),
dbc.Col(cats, width=4),
dbc.Col(datepick, width=4)
]
),
dbc.Row(
table
),
], style={'backgroundColor': '#faf9f9'}),
# graphs resulting from modified table
html.Div(dcc.Graph(id='key_graph_l'))
],
style={'backgroundColor': '#faf9f9'})
# add callback functions
@app.callback(
Output('datatable', 'data'),
[
Input('choose_cat', 'value'),
Input('choose_loc', 'value'),
Input('choose_date', 'start_date'),
Input('choose_date', 'end_date')
]
)
def update_table(choose_cat, choose_loc, start_date, end_date):
df = ti_data.copy()
df['date'] = pd.to_datetime(df['date'])
df['date'] = df['date'].dt.date
if choose_cat is not None:
df = df[df['category'] == choose_cat]
if choose_loc is not None:
df = df[df['locale'] == choose_loc]
if start_date is not None and end_date is not None:
start_date = datetime.datetime.strptime(start_date, "%Y-%m-%d").date()
end_date = datetime.datetime.strptime(end_date, "%Y-%m-%d").date()
df = df.loc[(df.date >= start_date) & (df.date <= end_date)]
data = df.to_dict('records')
return data
@app.callback(
Output('datatable', 'style_data_conditional'),
Input('datatable', 'selected_columns')
)
def update_styles(selected_columns):
return [{
'if': {'column_id': column},
'background_color': '#D2F3FF'
} for column in selected_columns]
@app.callback(
Output('key_graph_l', 'figure'),
[
Input('choose_date', 'start_date'),
Input('choose_date', 'end_date'),
Input('choose_cat', 'value'),
Input('choose_loc', 'value')
]
)
def update_key_l(choose_loc, choose_cat, start_date, end_date):
df = ti_data.copy()
if choose_cat is not None:
df = df[df['category'] == choose_cat]
if choose_loc is not None:
df = df[df['locale'] == choose_loc]
if start_date is not None and end_date is not None:
df = df.loc[(df.date >= start_date) & (df.date <= end_date)]
df = df.sort_values('total_count', ascending=False)[:25]
figure = px.scatter(df, x='keyword', y='date', color='locale', size='total_count',labels={'keyword': 'Keyword', 'total_count': 'Total Count', 'locale': 'Locale', 'date': 'Date'},
title='Weighing top words accross locales')
return figure
# requirements for beanstalk (aws)
if __name__ == '__main__':
app.run_server(debug=True)
