To create a facility maintenance dashboard using Python, you will need to follow these
steps:
1. Determine the data sources for your dashboard. This may include data from
maintenance logs, work orders, and equipment sensors, among others.
2. Clean and preprocess the data as necessary. This may involve removing missing
values, transforming data types, and performing calculations.
3. Choose a dashboarding library such as Plotly, Dash, or Bokeh, and install the
necessary dependencies.
4. Build the layout of the dashboard using the chosen library. This may involve
creating graphs, charts, and tables to display the data, as well as incorporating
interactive elements such as dropdowns, sliders, and date selectors.
5. Integrate the data with the dashboard by connecting to the data sources and
incorporating the cleaned and processed data into the dashboard layout.
6. Test the dashboard to ensure that it is functioning properly and providing the
desired insights.
7. Deploy the dashboard to a web server or cloud platform so that it can be accessed
by others in your organization.
Here is some sample code using the Plotly library to create a simple dashboard that
displays maintenance request data:
python
import pandas as pd
import plotly.express as px
import dash
import dash_core_components as dcc
import dash_html_components as html
df = pd.read_csv('maintenance_data.csv')
df['Request Date'] = pd.to_datetime(df['Request Date'])
app = dash.Dash(__name__)
app.layout = html.Div(children=[
html.H1(children='Facility Maintenance Dashboard'),