Issue
I am trying to come up with heatmap for correlation and I realized some are wrong.
Below is my heatmap. As you can see, the number for the action are not appearing.
This is my dataframe
all_gen_cols = steamUniqueTitleGenre[['action', 'adventure','casual', 'indie','massively_multiplayer','rpg','racing','simulation','sports','strategy']]
action adventure casual indie massively_multiplayer rpg racing simulation sports strategy
0 1 0 0 0 0 0 0 0 0 0
1 1 1 0 0 1 0 0 0 0 0
2 1 1 0 0 0 0 0 0 0 1
3 1 1 0 0 1 0 0 0 0 0
4 1 0 0 0 1 1 0 0 0 1
This is the code to produce the heatmap
def plot_correlation_heatmap(df):
corr = df.corr()
sb.set(style='white')
mask = np.zeros_like(corr, dtype=np.bool)
mask[np.triu_indices_from(mask)] = True
f, ax = plt.subplots(figsize=(11,9))
cmap = sb.diverging_palette(220, 10, as_cmap=True)
sb.heatmap(corr, mask=mask, cmap=cmap, vmax=0.3, center=0,
square=True, linewidths=.5, cbar_kws={"shrink": .5}, annot=True)
plt.yticks(rotation=0)
plt.show()
plt.rcdefaults()
plot_correlation_heatmap(all_gen_cols)
I am not sure what is the error.
print(all_gen_cols.corr())
The result for coorelation is below. I saw NaN for action but i am not sure why it is Nan.
action adventure casual indie massively_multiplayer rpg racing simulation sports strategy
action NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
adventure NaN 1.000000 0.007138 0.135392 0.023964 0.239136 -0.039846 0.036345 -0.064489 0.001435
casual NaN 0.007138 1.000000 0.235474 0.003487 -0.057726 0.079943 0.161448 0.149549 0.084417
indie NaN 0.135392 0.235474 1.000000 -0.082661 0.023372 0.045006 0.064723 0.056297 0.076749
massively_multiplayer NaN 0.023964 0.003487 -0.082661 1.000000 0.160078 0.036685 0.139929 0.018444 0.074683
rpg NaN 0.239136 -0.057726 0.023372 0.160078 1.000000 -0.046970 0.044506 -0.051714 0.097123
racing NaN -0.039846 0.079943 0.045006 0.036685 -0.046970 1.000000 0.127511 0.308864 -0.012170
simulation NaN 0.036345 0.161448 0.064723 0.139929 0.044506 0.127511 1.000000 0.212622 0.208754
sports NaN -0.064489 0.149549 0.056297 0.018444 -0.051714 0.308864 0.212622 1.000000 0.020048
strategy NaN 0.001435 0.084417 0.076749 0.074683 0.097123 -0.012170 0.208754 0.020048 1.000000
Below is by printing out print(all_gen_cols.describe())
action adventure casual indie massively_multiplayer rpg racing simulation sports strategy
count 14570.0 14570.000000 14570.000000 14570.000000 14570.000000 14570.000000 14570.000000 14570.000000 14570.000000 14570.000000
mean 1.0 0.362663 0.232189 0.657241 0.050927 0.165202 0.040288 0.121826 0.044269 0.127111
std 0.0 0.480785 0.422244 0.474648 0.219855 0.371376 0.196641 0.327096 0.205699 0.333108
min 1.0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
25% 1.0 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
50% 1.0 0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
75% 1.0 1.000000 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
max 1.0 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000
Data
This is the link to download the dataframe.
action,adventure,casual,indie,massively_multiplayer,rpg,racing,simulation,sports,strategy
1,0,0,0,0,0,0,0,0,0
1,1,0,0,1,0,0,0,0,0
1,1,0,0,0,0,0,0,0,1
1,1,0,0,1,0,0,0,0,0
1,0,0,0,1,1,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,1,0,0,1,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,1,1,0,0,0,1,0,1
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,1,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,1,1,0,0,0,0,0,0
1,1,1,1,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,1,0,1
1,1,0,0,1,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,1,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,1,0
1,0,0,1,1,0,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,1,0,1,0,0,0,0,0
1,0,1,0,1,0,0,0,1,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,1,0,1,0,1,0,1,0,1
1,0,1,1,1,0,0,0,0,1
1,1,1,1,0,0,0,0,1,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,1,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,1,0,1,0,0,0,1,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,1,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,1,0,1,1,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,1,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,1,0,0,0,0,0
1,1,0,1,1,0,0,1,0,1
1,0,0,0,0,0,0,1,0,0
1,1,0,0,0,0,0,1,0,0
1,1,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,1
1,1,0,1,1,0,0,1,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,0,0,0
1,1,1,1,0,0,0,0,0,1
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,1,0,1,1,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,1,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,1,0,0,0,0,0
1,0,0,0,1,0,0,1,0,1
1,1,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,1,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,0,1,1,0,1,0,1
1,0,0,1,1,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,1,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,1,1,1,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,1,0,0,0,0,1
1,0,0,1,0,1,0,1,0,1
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,0,0,0,1,0,1,0,0,0
1,1,0,1,0,1,0,0,0,0
1,1,0,1,0,1,0,1,0,1
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,1,1,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,1,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,1
1,1,0,1,0,1,0,1,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,0,0,1,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,0,0,0,1,0,0,1,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,0,1,1,0,1,0,1
1,0,0,1,0,0,0,1,0,1
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,1,0,1,0,0,0,1,0,0
1,0,1,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,1,0,1,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,1,1,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,1,0,1
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,1,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,1,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,0,0,1,0,0,0,1,0,1
1,1,0,0,1,1,0,1,0,1
1,1,0,1,1,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,0,0,1,0,0,1,0,1,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,1,1,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,0,0,1,0,0,0,1,0,0
1,1,0,1,1,1,0,1,0,1
1,0,0,1,0,1,0,0,0,0
1,1,1,0,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,1,0,0,0,0,0,0,0
1,0,0,0,1,1,0,0,0,0
1,0,1,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,1,1,0,0,0,1
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,1,0,0,0
1,1,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,1,1,1,0,1,0,0
1,1,0,0,0,0,0,0,0,0
1,1,1,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,1,0,0,1,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,1,1,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,1,0,0
1,0,0,0,1,0,0,0,0,0
1,1,0,1,1,1,0,0,0,0
1,1,0,0,0,1,1,1,1,0
1,1,0,1,0,0,0,1,0,1
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,0,0,0
1,0,0,0,0,0,0,1,0,0
1,1,0,0,1,1,0,0,0,0
1,0,0,0,0,0,0,1,0,1
1,1,0,1,1,0,0,1,0,1
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,1,0,0
1,1,1,1,1,1,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,0,0,1,0,1,0,0,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,1,0,0,0,1,0,0
1,0,1,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,1,0,1,0,0,0,1,0
1,1,0,1,0,1,0,0,0,0
1,0,0,0,0,0,0,1,0,1
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,0,0,0,0,1,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,1,1,0,0,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,0,1,1,0,0,0,0
1,0,0,0,0,0,1,1,1,0
1,0,0,0,0,1,0,0,0,1
1,0,0,0,1,0,1,0,0,0
1,0,0,1,0,1,0,0,0,1
1,1,0,0,0,0,0,1,1,0
1,0,0,1,0,0,0,0,0,1
1,1,0,0,0,1,0,0,0,0
1,0,0,1,0,0,0,1,0,1
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,1,0,1,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,1,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,1,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,0,0,0
1,1,1,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,0,0,0,0,1,0,0,0,0
1,1,1,1,1,1,0,0,0,1
1,1,0,1,0,1,0,0,0,0
1,0,0,1,0,1,0,0,0,1
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,1,0,0,0,0,1,0
1,1,1,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,1,1,0
1,0,0,1,0,0,0,1,1,0
1,1,1,1,1,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,1,1,1,0
1,1,0,0,1,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,1,1,1,1,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,1,0,1,1,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,1,0,1,0,0
1,0,0,1,0,0,0,0,0,0
1,1,1,1,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,1,0,0,1,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,1,0,0,0,0
1,1,0,1,0,1,0,1,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,0,0,0,0,0,0,1,0,1
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,1
1,0,1,1,0,0,0,0,0,0
1,1,0,0,1,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,1,0,0,1,0,0,0,1
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,1,0,0,1,0,1
1,0,0,1,1,0,0,1,0,1
1,1,0,0,1,1,0,1,0,1
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,1
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,1,0,1,0,0,0,1,0,0
1,0,0,0,1,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,1,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,1
1,1,0,1,0,0,0,1,0,0
1,0,0,0,0,0,1,1,1,0
1,1,1,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,1,0,1,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,1,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,1,0,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,1,0,0,0,0,0,0,0
1,0,0,1,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,1,0,0,0,0,1,1,0
1,0,0,0,0,0,0,0,0,0
1,1,1,1,0,1,0,0,0,0
1,1,0,1,0,1,0,1,0,1
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,1,0,1,1,1,0,0,0
1,0,0,1,0,0,0,1,0,0
1,1,0,1,0,0,0,1,0,0
1,0,1,1,0,1,1,1,0,1
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,1,1,1,0,1,0,1,0,0
1,1,0,1,0,0,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,1,0,1
1,0,0,0,1,0,0,1,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,1,0,1,0,1,0,0,0,0
1,0,1,1,0,0,1,0,1,0
1,0,0,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,1,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,1,1,0,0,0,0,0,0
1,1,1,1,0,0,0,1,0,0
1,1,0,1,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,0,0,1
1,1,0,0,0,0,1,0,0,0
1,0,0,1,0,0,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,1,0,1,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,1,0,0,0,1
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,1,1,0,0,0,0
1,0,0,0,0,0,1,0,1,0
1,1,0,1,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,1,1,1,1,1,0,1,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,0,1,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,0,1,0,0,0,0,0
1,0,1,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,1,1,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,1,0,0,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,1,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,1,0,0,0,1,0,1
1,1,0,0,0,0,0,0,0,0
1,0,0,0,1,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,1,1,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,0,0,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,1,1,0,0
1,1,0,1,0,0,1,1,0,0
1,0,0,1,0,1,0,0,0,1
1,1,1,0,1,0,0,0,0,0
1,0,0,1,0,0,0,1,0,1
1,1,0,0,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,0,0,1,0,1,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,0,1,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,1,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,1,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,1,0,0,1
1,0,0,1,0,0,0,1,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,1,1,0,0,0,1,0,0,0
1,0,1,1,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,1
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,1,0,1
1,0,0,1,0,0,0,1,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,1,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,1,1,0,0,0,0,0,1,1
1,0,1,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,1,0,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,1,0,0
1,0,0,1,0,0,0,0,0,1
1,1,0,1,1,0,0,1,0,1
1,0,0,1,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,1,0,0,0,1
1,0,0,1,0,0,0,1,0,0
1,0,0,1,0,0,0,0,1,1
1,0,0,1,0,0,0,1,0,1
1,0,1,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,1,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,1
1,0,0,0,0,1,0,0,0,0
1,1,1,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,1,0,1,1,1,0,0,0,0
1,0,0,0,0,0,0,1,0,0
1,1,0,1,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,1,0,0,1,0,1
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,1,1,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,1,0,1,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,0,1,0,1,0,0
1,0,0,1,0,0,0,0,0,1
1,0,0,1,0,0,0,1,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,1
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,1,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,1,0
1,1,0,1,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,0,1,1,0,0,0,0,0,0
1,0,1,1,0,0,0,1,0,1
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,1,1,1,0,1,1,1,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,1,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,1,1,0,0,0,0
1,1,0,1,0,0,0,1,0,1
1,1,0,1,0,0,1,1,0,0
1,0,0,0,0,1,0,0,0,1
1,1,0,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,1,0,1
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,1,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,1,1,0,1,0,0
1,1,1,0,1,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,1,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,0,0,1,0,1,0,1,0,0
1,1,0,0,1,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,1,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,1,1,0,0,0,1,0,0
1,0,0,1,0,0,1,0,0,0
1,1,1,0,0,1,1,0,1,1
1,1,0,0,0,0,0,0,0,0
1,1,1,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,1,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,1
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,0,1,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,0,0,1
1,0,0,1,0,0,0,0,0,1
1,0,0,1,0,1,0,0,0,0
1,1,1,1,0,0,0,0,0,1
1,0,1,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,0,0,1,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,1,1,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,1
1,1,0,1,0,1,0,0,0,0
1,1,1,1,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,1,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,0,0,1,0,0,0,0,0,1
1,1,0,0,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,0,0,1,1,0,1
1,1,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,0,0,1
1,0,0,0,0,1,0,0,0,0
1,0,1,1,0,0,0,1,0,1
1,0,1,0,0,0,1,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,1,1,0,0,1,0,1,0
1,1,0,1,1,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,0,0,1,0,1,0,0,0,0
1,1,1,1,0,1,0,1,0,1
1,1,0,1,0,1,0,0,0,0
1,1,1,1,0,1,0,1,0,0
1,1,0,1,0,0,0,0,0,0
1,0,1,0,1,0,0,1,0,1
1,0,1,0,1,0,0,1,0,1
1,0,0,1,0,0,0,0,0,1
1,1,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,1,0,1
1,0,0,0,1,0,0,0,0,0
1,1,0,0,0,0,0,0,0,1
1,0,0,0,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,0,0,1,0,0,0,1,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,1,1,0,0,0,0,0,0,1
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,1,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,1,0,0
1,0,1,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,0,0,0,1,0,0,1,0,0
1,0,0,0,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,1,0,0,0,1,0,1
1,1,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,1,1,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,1,1,0,0,0,1
1,0,0,1,0,0,0,1,1,1
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,1,0,0,1,0,1,0
1,0,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,0,0,1,0,0,0,0,0,0
1,1,1,0,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,0
1,1,0,1,0,0,0,0,0,1
1,1,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,1
1,0,0,0,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,1,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,0,1,0,1,0,0
1,0,0,0,0,1,0,0,0,0
1,1,0,1,0,0,0,1,0,1
1,0,0,0,1,0,1,0,0,0
1,1,1,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,1,1,0,0,0,1,0,0
1,0,0,1,0,0,0,0,0,0
1,1,1,1,0,1,0,1,0,0
1,0,0,0,0,0,0,1,0,1
1,0,0,1,0,0,0,1,1,0
1,0,0,1,0,1,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,1,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,1,0,1,0,1,0,0,0,0
1,0,1,1,0,0,0,0,1,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,0,1,1,0,0,0,0,1,0
1,1,0,0,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,1
1,0,0,1,0,0,0,0,0,1
1,1,0,1,1,1,0,0,0,0
1,0,0,1,0,0,0,1,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,1,1,1,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,0,0,0,0,0,0,1,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,1,1,1,0,0,1,1,1,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,1,1,0,0,0,1,0,1
1,0,0,1,0,0,0,0,0,0
1,0,0,1,0,0,0,0,1,0
1,1,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,1,0,1,0,0,0,0
1,0,1,1,0,0,1,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,1,0,1
1,1,0,1,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0,0,0
1,0,1,0,0,0,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,1,0,0,1,1,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,0,1,0,1,0,1,0,0
1,1,0,1,0,0,0,1,0,0
1,1,0,1,1,1,0,1,0,1
1,1,0,0,0,1,0,0,0,0
1,0,0,1,0,0,0,0,1,0
1,1,0,0,1,1,0,1,0,1
1,0,0,1,0,0,0,0,0,0
1,1,1,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,1,0,0,0,0
1,1,0,1,0,1,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,1,0,1,0,1,0,1,1,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,1,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,1
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,0,0,0,0,0,0,0,0,0
1,1,1,1,0,1,0,0,0,0
Solution
Seaborn doesn't show the rows and columns which are fully NaN; these are just left empty. It might look strange, but it is a perfectly logical behavior.
The correlation matrix sets the row and column corresponding to a constant value dataframe column to NaN.
A workaround could be to remove the NaN columns and rows, as suggested by @TrentonMcKinney, for example with corr = corr.dropna(how='all', axis=1).dropna(how='all', axis=0). Or remove the dataframe columns with zero variance (corr = df.loc[:, df.var().ne(0)].corr()).
Still another workaround, is to color the NaN values grey:
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
import seaborn as sns
import pandas as pd
import numpy as np
def plot_correlation_heatmap(df):
corr = df.corr()
sns.set(style='white')
mask = np.zeros_like(corr, dtype=bool)
mask[np.triu_indices_from(mask)] = True
f, ax = plt.subplots(figsize=(11, 9))
cmap = sns.diverging_palette(220, 10, as_cmap=True)
sns.heatmap(corr, mask=mask, cmap=cmap, vmax=0.3, center=0,
square=True, linewidths=.5, cbar_kws={"shrink": .5}, annot=True, ax=ax)
sns.heatmap(corr.fillna(0), mask=mask | ~ (np.isnan(corr)), cmap=ListedColormap(['lightgrey']),
square=True, linewidths=.5, cbar=False, annot=False, ax=ax)
ax.tick_params(axis='y', rotation=0)
plt.show()
plt.rcdefaults()
all_gen_cols = pd.DataFrame(np.random.randint(0, 2, size=(200, 10)), columns=[*'ABCDEFGHIJ'])
all_gen_cols['A'] = 1
plot_correlation_heatmap(all_gen_cols)
Answered By - JohanC
0 comments:
Post a Comment
Note: Only a member of this blog may post a comment.