def serve_layout():
return html.Div([
dbc.Alert(id="status_pseg", color='success'),
# Interval
dcc.Interval(interval=30 * 1000, id="interval_pseg"),
# Cards
dbc.Row(
[
dbc.Col(dbc.Card(first_card, color='info', outline=True)),
dbc.Col(dbc.Card(second_card, color='info', outline=True))
]),
dbc.Row(
[
dbc.Col(dbc.Card(third_card, color='primary', outline=True)),
dbc.Col(dbc.Card(fourth_card, color='primary', outline=True))
])
])
def serve_layout():
return html.Div([
# Interval
dcc.Interval(interval=30 * 1000, id="interval_seg"),
# Cards
dbc.Row([dbc.Col(dbc.Card(first_card, color="primary",
outline=True))]),
])
def serve_layout():
return html.Div([
# Status
dbc.Alert(id="status", color='success'),
# Interval
dcc.Interval(interval=30 * 1000, id="interval"),
# Cards
dbc.Row([dbc.Col(first_card, width=6),
dbc.Col(second_card, width=6)])
])
import pathlib
#---------------------------------------------------------------
PATH = pathlib.Path(__file__).parent
DATA_PATH = PATH.joinpath("../data").resolve()
df_pandas = pd.read_csv(DATA_PATH.joinpath("train.csv"),parse_dates=['publish_date'])
#category_x = ['category_id', 'country_code']
value_y = ['views', 'dislikes','comment_count']
#-------------------------------------------------------------------------------------
style = {'padding': '1.5em'}
layout = dbc.Container([
html.Br(),
dbc.Row([
dbc.Col(
html.H2("Bar Chart for Country and Video Category",
className="text-center font-weight-normal text-primary"))
#style={"text-align": "center", "font-size":"100%", "color":"black"}))
]),
#-------------------------------------------------------------------------------------
dbc.Row([
dbc.Col([
html.Label(['X-axis categories to compare:'],style={'font-weight': 'bold'}),
dcc.RadioItems(id='xaxis_raditem',
options=[{'label': 'Video Category', 'value': 'category_id'},
{'label': 'Country', 'value': 'country_code'}],
value='country_code',
className="font-weight-normal text-primary",
style={"width": "50%"}),
],width=8),
]),
#-------------------------------------------------------------------------------------
import dash_html_components as html
from app import app, dbc
layout = dbc.Container(
[
dcc.Markdown('### Final Results'),
dbc.Row([
dbc.Col([
html.
H6("Feature Importance for predicting youtube likes (Descending Order)"
),
html.Img(
src=
'https://raw.githubusercontent.com/ianuvrat/datasets/main/download.png'
),
],
className="text-center",
width={
'size': 12,
'offset': 0,
'order': 1
}),
]),
#-----------------------------------------------------------------------
html.Br(),
dbc.Row([
dbc.Col([
html.H6(""" Pearson Correlation Matrix """),
html.Img(
src=
dbc.Row([
dbc.Col([
dash_table.DataTable(
id='datatable_id',
data=dff.to_dict('records'),
columns=[
{"name": i, "id": i, "deletable": True, "selectable": True, "hideable": True}
if i == "video_id" or i == "publish_date" or i == "title" or i == "channel_title" or i == "description" or i == "tags"
else {"name": i, "id": i, "deletable": True, "selectable": True}
for i in dff.columns
],
editable=False, # allow editing of data inside all cells
filter_action="native", # allow filtering of data by user ('native') or not ('none')
sort_action="native", # enables data to be sorted per-column by user or not ('none')
sort_mode="multi", # sort across 'multi' or 'single' columns
column_selectable="multi", # allow users to select 'multi' or 'single' columns
row_selectable="multi", # allow users to select 'multi' or 'single' rows
row_deletable=False, # choose if user can delete a row (True) or not (False)
selected_columns=[], # ids of columns that user selects
selected_rows=[], # indices of rows that user selects
page_action='native',
style_cell={'whiteSpace': 'normal', 'minWidth': 95, 'maxWidth': 95, 'width': 95},
fixed_rows={'headers': True, 'data': 0},
virtualization=False,
style_cell_conditional=[ # align text columns to left. By default they are aligned to right
{
'if': {'column_id': c},
'textAlign': 'left'
} for c in ['country', 'iso_alpha3']
],
style_data={ # overflow cells' content into multiple lines
'whiteSpace': 'normal',
'height': 'auto'
},
)
]) ,
]),
placeholder='Select a date',
date=dt(2020, 3, 13)),
className="d-inline p-2 bg-dark text-white")
]),
html.Div([
dcc.Graph(id="coil_gait_chart", style={
"overflowY": "scroll",
}),
])
])
]
""" Top Element """
alert = dbc.Alert([
dbc.Row([
dbc.Col(
html.H2("TCM Coil Production Performance",
className="alert-heading")),
dbc.Col(html.H6(id="status_prod", className="alert-heading")),
]),
html.Hr(),
dbc.Row([
dbc.Col(html.Div(
dcc.DatePickerRange(id='date-picker-range',
min_date_allowed=dt(2017, 8, 5),
max_date_allowed=dt.now(),
initial_visible_month=dt.now(),
end_date=dt.now())),
width="auto"),
dbc.Col(html.Div(
dbc.Button(id='submit-button',
n_clicks=0,
children='Submit',
country_code = ['IN', 'CA', 'US', 'GB']
category_id = [24.0, 25.0, 22.0, 10.0]
style = {'padding': '1.5em'}
alert = dbc.Alert("Prectiction using XGBoost model is better!",
color="danger",
duration=3000)
# dismissable=False), # use dismissable or duration=5000 for alert to close in x milliseconds
#-----------------------------------------------------------------------
layout = dbc.Container(
[
html.Br(),
dbc.Row([
dbc.Col([
html.
H6("Estimate the number of likes your youtube video can get, based on different parameters.",
className="text-dark")
])
]),
#-----------------------------------------------------------------------
dbc.Row([
dbc.Col(
[
html.Div(id="the_alert", children=[]),
html.Label(['Prediction Model:'],
style={'font-weight': 'bold'}),
dcc.RadioItems(id='xaxis_raditem',
options=[{
'label': 'XGBoost',
'value': 'XGBoost'
}, {
bargap=0.15, # gap between bars of adjacent location coordinates.
bargroupgap=0.1 # gap between bars of the same location coordinate.
)
return {"data": data, "layout": layout}
def default_layout_null():
return html.Div(style={'display': 'none'})
""" Layout Elements"""
""" Top Element """
alert = dbc.Alert([
dbc.Row([
dbc.Col(html.H2("PLTCM Plant Performance", className="alert-heading")),
dbc.Col(html.H6(id="status_stop", className="alert-heading")),
]),
html.Hr(),
dbc.Row([
dbc.Col(html.Div(
dcc.DatePickerRange(id='date-range',
min_date_allowed=dt(2017, 8, 5),
max_date_allowed=dt.now(),
initial_visible_month=dt.now(),
end_date=dt.now())),
width="auto"),
dbc.Col(html.Div(
dbc.Button(id='submit-button',
n_clicks=0,
children='Submit',
color="primary",