Cómo trazar el mapa de calor en Python
import seaborn as sns
f,ax = plt.subplots(figsize=(20, 20))
sns.heatmap(df.corr(), annot = True, fmt= '.2f')
Sleepy Scarab
import seaborn as sns
f,ax = plt.subplots(figsize=(20, 20))
sns.heatmap(df.corr(), annot = True, fmt= '.2f')import numpy as np
import seaborn as sns
import matplotlib.pylab as plt
uniform_data = np.random.rand(10, 12)
ax = sns.heatmap(uniform_data, linewidth=0.5)
plt.show()Plotly
https://youtu.be/RgRwsKjkJnUcorrelation=df.corr()
sns.heatmap(correlation,cbar=True,square=True,fmt='.1f',annot=True,annot_kws={'size':8},cmap="Blues")
# Does this work for you?
# was gonna use numpy
import numpy as np
# Anyways, defining the function
def heatmap(data, row_labels, col_labels, ax=None,
cbar_kw={}, cbarlabel="", **kwargs):
# Create a figure if we do not have one
if ax is None:
fig, ax = plt.subplots()
# Create a heatmap
im = ax.imshow(data, **kwargs)
# Create colorbar
cbar = ax.figure.colorbar(im, ax=ax, **cbar_kw)
cbar.ax.set_ylabel(cbarlabel, rotation=-90, va="bottom")
# We want to show all ticks
ax.set_xticks(np.arange(len(col_labels)))
ax.set_yticks(np.arange(len(row_labels)))
# We want to label ticks with the respective list entries
ax.set_xticklabels(col_labels)
ax.set_yticklabels(row_labels)
# Let the horizontal axes labeling appear on top
ax.tick_params(top=True, bottom=False,
labeltop=True, labelbottom=False)
# Rotate the tick labels and set their alignment.
plt.setp(ax.get_xticklabels(), rotation=-30, ha="right", rotation_mode="anchor")
# Turn spines off and create white grid.
for edge, spine in ax.spines.items():
spine.set_visible(False)
ax.set_xticks(np.arange(data.shape[1]+1)-.5, minor=True)
ax.set_yticks(np.arange(data.shape[0]+1)-.5, minor=True)
ax.grid(which="minor", color="w", linestyle='-', linewidth=1)
ax.tick_params(which="minor", bottom=False, left=False)
return im, cbar # return the image and colorbar