How to maintain pie chart legend colors consistent.

Hi  Rockz , 

I'm afraid the pie chart visual cannot set fixed colors for a dynamic category, but you might consider using a Python visual to achieve this. I've made a test for your reference:

1\My data source(Table):

Category Column

 

 

Category = 
VAR X = MAX('Table'[Value])
VAR Achieve_mins = X * 3 * 60
RETURN
IF(
[Status] IN {"Closed", "Completed"} && [ProcessingTime_Mins] <= Achieve_mins,
"Closed within " & X & " days",
IF(
[Status] IN {"Closed", "Completed"} && [ProcessingTime_Mins] > Achieve_mins,
"Closed more than " & X & " days",
IF(
[Status] IN {"Started", "New"} && [ProcessingTime_Mins] <= Achieve_mins,
"Open within " & X & " days",
IF(
[Status] IN {"Started", "New"} && [ProcessingTime_Mins] >Achieve_mins,
"Open more than " & X & " days",
"Unknown"
)
)
)
)

 

 

 2\Add a python visual

 

 

 

# The following code to create a dataframe and remove duplicated rows is always executed and acts as a preamble for your script: 

# dataset = pandas.DataFrame(Category, ID, ProcessingTime_Mins, Status, Value)
# dataset = dataset.drop_duplicates()

# Paste or type your script code here:

import matplotlib.pyplot as plt
import pandas as pd

# Assign colors based on the starting characters of the Category string
def get_color(row):
    category = row['Category']

    # Use str.startswith() to check the starting characters
    if category.startswith(('Open within')):
        return "red"
    elif category.startswith(('Open more')):
        return "green"
    elif category.startswith(('Closed within')):
        return "yellow"
    elif category.startswith(('Closed more')):
        return "blue"
    else:
        return "black"  # Default color

# Apply color rules
dataset['Color'] = dataset.apply(get_color, axis=1)

# Count the number of records for each Category
category_counts = dataset['Category'].value_counts()

# Ensure the color order matches the categories
colors = [dataset[dataset['Category'] == category]['Color'].iloc[0] for category in category_counts.index]

# Generate pie chart
fig, ax = plt.subplots()
ax.pie(category_counts, labels=category_counts.index, colors=colors, autopct='%1.1f%%')

# Display the pie chart
plt.show()

 

 

Note: Before using Python visuals, you need to first install R and Python locally, and then install the matplotlib and pandas libraries.

R: https://cran.r-project.org/bin/windows/base/

Python: https://www.python.org/downloads/

How to set Windows environment variables for Python: https://www.youtube.com/watch?v=Y2q_b4ugPWk

How to Install numpy, pandas and matplotlib Python libraries on Windows:

Enter the following command in the command line

pip install matplotlib pandas

https://www.youtube.com/watch?v=2iswYOPEeHk

 

Best Regards,

Bof