Emilio Conde

Thanks for the context, John.
 
Unfortunately, Organizer currently only supports basic html, and not CSS / HTML5 as implemented by the .highlight_max() or .highlight_null operators.
 
With that said, I recommend you send us a support ticket here requesting this functionality so that we can link it to an existing feature request and allow you to be automatically notified of this capability once it's implemented in a future version of Seeq.
 
Working with ChatGPT, I was able to get the basic HTML equivalent applied to the df in your example, and have verified it pushes to Organizer as expected. Of course, another approach could be to create an image out of your html and just push the image. There are other posts on this forum that discuss that functionality.
See working example below:
import numpy as np import pandas as pd from bs4 import BeautifulSoup organizer_id = '7AC3EAA0-6429-46D5-88E3-57ADC6AA1ED7' df = pd.DataFrame({ "A": [0, -5, 12, -4, 3], "B": [12.24, 3.14, 2.71, -3.14, np.nan], "C": [0.5, 1.2, 0.3, 1.9, 2.2], "D": [2000, np.nan, 1000, 7000, 5000] }) # Basic HTML to highlight a cell def highlight_cell_bg(val, color=None): # If there's a color specified, apply it as the background if color: return 'background-color: {}'.format(color) return "" # Highlight the max value in a column yellow def highlight_max_bg(series): # Remove non-numeric values and compute max numeric_vals = series[pd.to_numeric(series, errors='coerce').notnull()] if not numeric_vals.empty: max_val = numeric_vals.max() return [highlight_cell_bg(val, 'yellow') if val == max_val else "" for val in series] return [""] * len(series) # Highlight Missing row values red def highlight_missing_bg(val): if val == 'Missing': return highlight_cell_bg(val, 'red') return "" # Replace NaN values with "Missing" and highlight them df.replace({np.nan: 'Missing'}, inplace=True) missing_bg = df.applymap(highlight_missing_bg) # Highlight the maximum values in each column max_bg = df.apply(highlight_max_bg) # Merge the two background styles final_bg = missing_bg.where(missing_bg != "", max_bg) # Convert DataFrame to HTML without additional formatting raw_html = df.to_html(escape=False, header=True, index=False) # Parse the HTML using BeautifulSoup soup = BeautifulSoup(raw_html, 'html.parser') # Iterate through each cell in the table and apply styles for row in soup.findAll("tr"): for col_name, cell in zip(df.columns, row.findAll("td")): if cell.text in df.columns: continue # Skip headers # Convert dataframe values to string for comparison idx = df[col_name].astype(str).tolist().index(cell.text) style = final_bg[col_name].iloc[idx] if style: cell["style"] = style # Convert the modified HTML back to a string html = str(soup) # Find the topic you want topic_search = spy.workbooks.search({'ID': organizer_id}) # Pull in the topic topic = spy.workbooks.pull(topic_search, include_referenced_workbooks = False)[0] # Create a new sheet topic.document('New Sheet') # Modify the html of the new sheet with the styled df html topic.worksheets[-1].html = html # Push your changes organizer_push = spy.workbooks.push(topic)