Slider in `scatter_3d` and `scatter` makes some data points go missing
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 18.8k
- Forks
- 2.8k
- Avg merge
- 16h 26m
- Merged PRs (30d)
- 21
Description
Only 2 out of 4 categories are plotted when I use a slider. Other data points do not appear at all. When I slide the slider, different categories are plotted. E.g. in the MWE below, only TP and FP show up when the slider is below 0.9. At 0.9 only TN and FN show up.
This behavior also happens for both 2d and 3d scatter plots. See the MWE below for 3d.
import numpy as np
import pandas as pd
import plotly.express as px
def plot_scatter_3d_mwe():
# Create a small DataFrame with fake data
data = {
'Dim1': np.random.rand(10),
'Dim2': np.random.rand(10),
'Dim3': np.random.rand(10),
'due': [1, 0, 1, 0, 1, 0, 1, 0, 1, 0],
'serial_number': range(10),
'predicted_probabilities': [0.9, 0.8, 0.4, 0.2, 0.6, 0.7, 0.1, 0.5, 0.3, 0.95]
}
df = pd.DataFrame(data)
thresholds = np.arange(0, 1.1, 0.1)
all_frames = []
for threshold in thresholds:
# Recalculate predictions based on the threshold
predicted = (df['predicted_probabilities'] >= threshold).astype(int)
# Create the 4 categories for coloring: TP, TN, FP, FN
conditions = [
(df['due'] == 1) & (predicted == 1), # TP
(df['due'] == 0) & (predicted == 0), # TN
(df['due'] == 0) & (predicted == 1), # FP
(df['due'] == 1) & (predicted == 0), # FN
]
categories = ['TP', 'TN', 'FP', 'FN']
# Assign the categories to a new column
df['category'] = np.select(conditions, categories, default='Unknown')
df['threshold'] = threshold # Add threshold as a column for animation frame
all_frames.append(df.copy())
# Concatenate all frames for animation
df_all_frames = pd.concat(all_frames)
# Plot the scatter 3D with the categories as color and animate over thresholds
fig = px.scatter_3d(df_all_frames,
x='Dim1', y='Dim2', z='Dim3',
color='category',
animation_frame='threshold',
animation_group='serial_number')
fig.show()
# Call the function
plot_scatter_3d_mwe()
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Run the provided Python MWE in plot_scatter_3d_mwe and compare the animated 2D and 3D scatter behavior across threshold frames. Trace how animation_frame and animation_group are represented in the generated figure; done means all four categories and their data points remain available at every slider position.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- numpy, pandas, plotly, python
- Domain
- data-visualization
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100