Seaborn pairplot and NaN values

Question

I'm trying to understand why this fails, even though the documentation says:

dropna : boolean, optional Drop missing values from the data before plotting.

from matplotlib import pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
sns.__version__
# '0.7.dev'
# generate an example DataFrame
a = pd.DataFrame(data={
    'a': np.random.normal(size=(100,)),
    'b': np.random.lognormal(size=(100,)),
    'c': np.random.exponential(size=(100,))})
sns.pairplot(a) # this works as expected
# snip
b = a.copy()
b.iloc[5,2] = np.nan # replace one value in col 'c' by a NaN
sns.pairplot(b) # this fails with error 
                # "AttributeError: max must be larger than min in range parameter."
                # in histogram(a, bins, range, normed, weights, density)"
> sns.pairplot(b, dropna=True) # same error as above

Answer 1

when you are using the data directly, ie

sns.pairplot(b) #Same as sns.pairplot(b, x_vars=['a','b','c'] , y_vars=['a','b','c'],dropna=True)

your are plotting against all the columns in the DataFrame,Then make sure no:of rows are same in all columns.

sns.pairplot(b, x_vars=['a','c'] , y_vars=['a','b','c'],dropna=True)

In this case it works fine, but there will be a minute difference in the graph for removing the 'NaN value'.

So, If you want to plot with the whole Data then :-

• either the null values must be replaced using "fillna()",

• or the whole row containing 'nan values' must be dropped

  b = b.drop(b.index[5])
  sns.pairplot(b)