Python, Seaborn: how to replicate corrplot?

First, the fact that corrplot() is depreciated does not mean that you cannot use it. It is just likely that it will be removed in some future version of seaborn or has some other issue accompanying it. However, if you are happy with what it gives you now, you may still use it.

In order to get a result similar to the corrplot but using a heatmap, you may need to tweak the plot a bit.

An example is shown below:

import numpy as np; np.random.seed(1)
import pandas as pd
import seaborn.apionly as sns
import matplotlib.pyplot as plt

# Generate a random dataset
cols = [s*4 for s in list("ABCD")]
df = pd.DataFrame(data=np.random.rayleigh(scale=5, size=(100, 4)), columns=cols)

# Compute the correlation matrix
corr = df.corr()
print(corr)
# Generate a mask for the upper triangle
mask = np.zeros_like(corr, dtype=np.bool)
mask[np.triu_indices_from(mask)] = True

# Set up the matplotlib figure
fig, ax = plt.subplots()

# Draw the heatmap with the mask and correct aspect ratio
vmax = np.abs(corr.values[~mask]).max()
sns.heatmap(corr, mask=mask, cmap=plt.cm.PuOr, vmin=-vmax, vmax=vmax,
            square=True, linecolor="lightgray", linewidths=1, ax=ax)
for i in range(len(corr)):
    ax.text(i+0.5,len(corr)-(i+0.5), corr.columns[i], 
            ha="center", va="center", rotation=45)
    for j in range(i+1, len(corr)):
        s = "{:.3f}".format(corr.values[i,j])
        ax.text(j+0.5,len(corr)-(i+0.5),s, 
            ha="center", va="center")
ax.axis("off")
plt.show()

this simple thing below gets me a corrplot. Now you can play with map_upper and map_lower and generate what you want.

tech_rets_corr= tech_rets.dropna().corr()
sns.heatmap(tech_rets_corr, annot=True, fmt='.2f')
plt.show()