python - FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated use `arr[tuple(seq)]`

Question

I have searched S/O but I couldn't find a answer for this.

When I try to plot a distribution plot using seaborn I am getting a futurewarning. I was wondering what could be the issue here.

import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
% matplotlib inline
from sklearn import datasets

iris = datasets.load_iris()
df = pd.DataFrame(iris.data, columns=iris.feature_names)
df['class'] = iris.target
df['species'] = df['class'].map({idx:s for idx, s in enumerate(iris.target_names)})


fig, ((ax1,ax2),(ax3,ax4))= plt.subplots(2,2, figsize =(13,9))
sns.distplot(a = df.iloc[:,0], ax=ax1)
sns.distplot(a = df.iloc[:,1], ax=ax2)
sns.distplot(a = df.iloc[:,2], ax=ax3)
sns.distplot(a = df.iloc[:,3], ax=ax4)
plt.show()

This is the warning:

C:\ProgramData\Anaconda3\lib\site-packages\scipy\stats\stats.py:1713:
FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; 
use `arr[tuple(seq)]` instead of `arr[seq]`. 
In the future this will be interpreted as an array index, `arr[np.array(seq)]`,
which will result either in an error or a different result.
return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval

Any help? You can run the above code. You'll get the warning.

Pandas : 0.23.4, seaborn : 0.9.0, matplotlib : 2.2.3, scipy : 1.1.0, numpy: 1.15.0'

Answer 1

A fuller traceback would be nice. My guess is that seaborn.distplot is using scipy.stats to calculate something. The error occurs in

def _compute_qth_percentile(sorted, per, interpolation_method, axis):
    ....
    indexer = [slice(None)] * sorted.ndim
    ...
    indexer[axis] = slice(i, i + 2)
    ...
    return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval

So in this last line, the list indexer is used to slice sorted.

In [81]: x = np.arange(12).reshape(3,4)
In [83]: indexer = [slice(None), slice(None,2)]
In [84]: x[indexer]
/usr/local/bin/ipython3:1: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  #!/usr/bin/python3
Out[84]: 
array([[0, 1],
       [4, 5],
       [8, 9]])
In [85]: x[tuple(indexer)]
Out[85]: 
array([[0, 1],
       [4, 5],
       [8, 9]])

Using a list of slices works, but the plan is to depreciate in the future. Indexes that involve several dimensions are supposed to be tuples. The use of lists in the context is an older style that is being phased out.

So the scipy developers need to fix this. This isn't something end users should have to deal with. But for now, don't worry about the futurewarning. It doesn't affect the calculations or plotting. There is a way of suppressing future warnings, but I don't know it off hand.

FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated use `arr[tuple(seq)]` instead of `arr[seq]`

Answer 2

For python>=3.7 you need to upgrade your scipy>=1.2.

Answer 3

I was running seaborn.regplot, and got rid of the warning by upgrading scipy 1.2 as NetworkMeister suggested.

pip install --upgrade scipy --user

If you still get warnings in other seaborn plots, you can run the following beforehand. This is helpful in Jupyter Notebook because the warnings kind of make the report look bad even if your plots are great.

import warnings
warnings.filterwarnings("ignore")

Answer 4

I came across the same warning. I updated scipy,pandas and numpy. I still get it.I get it when i use seaborn.pairplot with kde, which underneath uses seaborn.kdeplot.

If you want to get rid off the warning you can use warnings library. Ex:

import warnings

with warnings.catch_warnings():

    your_code_block

Answer 5

Working example :

import numpy as np
import warnings

x  = np.random.normal(size=100)

with warnings.catch_warnings():
    warnings.simplefilter("ignore")
    
    sns.distplot(x, hist=False, rug=True, color="r");