# Tag Info

Accepted

### make seaborn heatmap bigger

I found out how to increase the size of my plot with the following code... plt.subplots(figsize=(20,15)) sns.heatmap(corr)
• 631

### What is this type of plot and how to interpret it?

The shaded area likely shows the dark green line plus or minus some error/uncertainty estimate. Common error estimates may be based on the standard deviation, a confidence interval, or the ...
• 342

### Scatter plot for binary class dataset with two features in python

One approach is to plot the data as a scatter plot with a low alpha, so you can see the individual points as well as a rough measure of density. ...
• 2,470
Accepted

### Data Visualization with multiple dimension, and linear separability

You basically need a t-SNE plot, the t-SNE will convert the high dimensional feature vector (several features in your case) to a 2d point and then you can use matplotlib to plot, while plotting you ...

### Data Visualization with multiple dimension, and linear separability

When class labels are known, you can use Linear Discriminant Analysis (LDA) for visualization to see whether classes are linearly separable. LDA is similar to PCA but supervised. It tries to project ...
• 9,372
Accepted

### How to interpret Shapley value plot for a model?

1. 2. not always there are some blue points also. 3. 4. 5. yes 6. it depends on the shap plot you are using, on some them default is to surpress less important features and not even plot them. 7. ...
• 5,719

### What is this type of plot and how to interpret it?

It might be plus or minus one standard deviation. But it could be anything really. Without more context you can't be sure.
• 151

### make seaborn heatmap bigger

This would also work. plt.figure(figsize=(20,15)) ax=subplot(111) sns.heatmap(corr,ax=ax)
• 505

### Plots with shaded standard deviation

The below piece of code will generate the following Image(your's is Subplotting Three of them, so you will get 3 different axe's and per axes you have to use fill-between) (Kindly ignore the Axis ...
• 2,470
Accepted

• 91
Accepted

### Plotting in PySpark?

No, there is no such method, I have found out. The reason is, plotting libraries run on a single machine and expect a rather sample dataset. Data on Spark is distributed among its clusters and hence ...
• 599
Accepted

### Plotting multiple precision-recall curves in one plot

Try using Matplotlib gca() method in this way you can indicate what axis you want to plot in ...
• 3,009

### Plotly, scatter plot: what are the possible options for the dash entry in the line dictionary?

When I put an invalid value to the 'dash' property, plotly shows an error message that list all the admissible values: The 'dash' property is an enumeration that may be specified as: ...

### Looping problem in python

In your specific case you only have 2 clusters, however this is not necessarily always going to be the case. I would allow for more flexibility. I assume from your sample code that you are following ...
• 8,976

### Validation curve unlike SKLearn sample

This is exactly your code just with digits data: ...
• 6,612

### Smooth curve in Bokeh

bokeh library internally uses _glyph_function function to plot, if you take a look at their source code and which takes help ...
• 1,799

### How to plot clusters in nice a way?

T-SNE is another dimensionality reduction algorithm not mentioned in the article in the other answer. Used for VERY high dimensional data, if you have trained some embeddings for your dataset. ...
• 571

### How to plot clusters in nice a way?

Several options: Locally Linear Embedding (LLE): This method construct a set of local geometric patches on each of which a data point is reconstructed through the weighted sum of its K nearest ...
• 6,612
Accepted

### Name of this type of cross variable interaction Plot

Here is python code to make a pretty good match for your picture. ...
• 303
Accepted

### How can I get variable values from a plot?

It seems what you are looking for is a function of your data, not of matplotlib. I would think of this as a second derivative problem -- you care about differences ...

### Is my iPython Installation Valid?

It looks fine to me :) the only problem is that your plot (resulting from In [18]) is being displayed on your computer in a separate window somewhere - maybe you ...
• 15k

### What is this type of plot and how to interpret it?

Without more information it is hard to say for certain, but my best guess is that the shaded region is a confidence interval (say ± 1 standard deviation) around the predicted values which are ...
• 354
Accepted

• 7,987

### How pairplot is constructed? Based on what rule? Why people use it?

Differences: Pairplot If you have m attributes in your dataset, it creates a figure with (m)x(m) subplots. The main-diagonal subplots are the univariate histograms (distributions) for each ...
• 3,970

### Finding similarity between two histogram plots

I'm curious what other people will say, but one option is to use KL-divergence. If your two histograms have the same x-axis, you can divide every column by the total count to convert counts to ...
• 2,248

### How to plot similarity of two datasets?

Here we have 50000 points, 10000 in each of five categories with associated numerical values....
• 2,470
Accepted

### How to plot similarity of two datasets?

Here is an example of r lattice xyplot using log scale on the x axis and the difference of your two measures ...
• 1,113
Accepted

### Data Visualisation for Dataframe having 3 columns

use matplotlib: ...
• 186