It seems to me the heatmap function is applied to the dataframe in its entirety. What if I only want the heatmap applied to a given set of column(s) from my dataset? I would imagine this can be achieved by smartly using cmap, but cannot seem to get it to work.
Pass the desired sub-DataFrame to seaborn.heatmap
:
seaborn.heatmap(df[[col1, col2]], ...)
df[[col1, col2, ..., coln]]
returns a DataFrame composed of the columns col1
, col2
, ... coln
from df
. Note the double brackets.
If you wish to highlight only certain values and plot the heatmap as though all other values are zero,
you could make a copy of the DataFrame and set those values to zero before calling heatmap
. For example, modifying the example from the docs,
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import seaborn.matrix as smatrix
sns.set()
flights_long = sns.load_dataset("flights")
flights = flights_long.pivot("month", "year", "passengers")
flights = flights.reindex(flights_long.iloc[:12].month)
columns = [1953,1955]
myflights = flights.copy()
mask = myflights.columns.isin(columns)
myflights.loc[:, ~mask] = 0
arr = flights.values
vmin, vmax = arr.min(), arr.max()
sns.heatmap(myflights, annot=True, fmt="d", vmin=vmin, vmax=vmax)
plt.show()
yields
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