import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
np.random.seed(2015)
N = 100
arr = np.random.random((N, 2)) * np.logspace(-2, 2, N)[:, (np.newaxis)]
data = pd.DataFrame(arr, columns=['kppawr23', 'kppaspyd'])
bins = np.logspace(-2, 2, 20)
axs = data.hist(bins=bins)
for ax in axs.ravel():
    ax.set_xscale('log')
plt.gcf().tight_layout()
plt.show()
Want to plot Pandas Dataframe as Multiple Histograms with log10 scale x-axis