Error creating heatmap from data frame with seaborn

Question

I am trying to create a heat map from a data frame. Each column I am using is made up of numpy.float64.

def create_visual(x, y , z,aggfunc = 'mean'):
    bip_2 = bip[[x,y,z]]
    bip_2 = bip_2.pivot_table(index=x, columns=y, values=z, aggfunc=aggfunc)
    ax = sns.heatmap(bip_2)

Each column is a list of numpy.float64. The error I am recieving is:

TypeError: float() argument must be a string or a number, not 'NAType'

The data frame is:

	hc_x1	hc_y1	delta_run_exp
3171	152.0	155.0	-0.082
3340	145.0	148.0	-0.134
1632	155.0	174.0	-0.309
1776	20.0	106.0	0.422
1892	168.0	61.0	-0.207
...	...	...	...
3782	136.0	150.0	-0.349
1759	155.0	172.0	-0.390
2681	99.0	176.0	-0.566
3241	65.0	122.0	0.700
3408	87.0	110.0	0.327

Thank you.

Answer 1

NAType in Pandas typically represents missing data. Have you checked to see if there is any missing data in your DataFrame?

You can do this for the whole DataFrame with df.isnull().values.any().

For example:

frame = pd.DataFrame({'col1' : [1, 2, 3, None], 'col2' : ['a', None, 'b', 'c']})
check = frame.isnull().values.any()
print(check)

If you find that you have NaN values, you can be more specific in that query and find the columns and rows. Pandas also lets you replace NaN values with df.fillna() or drop them with df.dropna().