matplotlib contourf plot sparsity whitespace, need interpolation?

Question

I have a set of data captured in a pandas data frame which I would like to plot on a contourf plot. When plotting, I can see much white space in certain areas of the contour which I'm not sure how to fix. My x-data is semilog. I'm not sure if some kind of interpolation would help, or if it is someway I am generating my mesh grid and contour itself. I will attach an image and 2 sets of data frames as examples.

contourplot

Data file can be found here: https://drive.google.com/drive/folders/13aO1_P0wzLCjZSTIgalXyaR4cdW1_Rh8?usp=sharing

import os,sys
import numpy as np
import pandas as pd
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt

#dev
import pprint
np.set_printoptions(threshold=sys.maxsize)
np.set_printoptions(suppress=True)


# start
Data = pd.read_csv('DF.csv',index_col=0)
plt.rcParams['figure.figsize'] = (16,10)
Freqs = Data.iloc[:,0]      # Frequencies for data
angleFullset= ['{:03}'.format(x) for x in [*range(0,360,15)]]   # test set, name of df cols in degrees
angleContour = [[int(x) for x in angleFullset],[int(x) if int(x) < 181 else int(x) - 360 for x in angleFullset]]    # rename colum names to -180 to 180 deg
angleContour[0].append(angleContour[0][0]); angleContour[1].append(angleContour[1][0] - 1)  # append 1 more column for last data set (which is same as first)
idx_180 = angleContour[1].index(180)
angleContour[0].insert(idx_180 + 1,-180); angleContour[1].insert(idx_180 + 1,-180)          # insert another column after 180 to cover -180 case

[X,Y] = np.meshgrid(Freqs,angleContour[1])
fig,ax = plt.subplots(1,1)
ax.semilogx()
plt.hlines(0,20,20000,'k',linewidth=1.5)      # zero axis 
plt.vlines(100,-200,200,'k',linewidth=2)      # 100Hz axis
plt.vlines(1000,-200,200,'k',linewidth=2)     # 1kHz axis
plt.vlines(10000,-200,200,'k',linewidth=2)    # 10kHz axis
plt.xlim([85,8000])
plt.ylim([-180,180])
plt.xticks([100,1000,8000],('100','1000','8000'))
plt.yticks(range(-180,181,30))  
plt.xlabel('Frequency [Hz]')
plt.ylabel('Angle [deg]')
plt.grid(b=True,which='major'); plt.grid(b=True,which='minor')
plt.title('Contour')

newData = Data.copy()
newData.drop("Freq",axis=1,inplace=True)
newData['001'] = newData['000']                                             # for data from -345 to 0
newData.insert(newData.columns.get_loc('180')+1,'-180',newData['180'])      # for data from -180 to -165
lev_min,lev_max,levels = -70,-19,range(-70,-19,1)

CM = ax.contourf(X,Y,newData.transpose(),cmap=matplotlib.cm.jet,levels=levels,vmin=lev_min,vmax=lev_max)
plt.colorbar(CM,label='Magnitude [dB]',fraction=0.1)

outputFileName = os.path.join(os.getcwd(),'Contour.png')
plt.savefig(outputFileName,orientation='landscape',format='png')
plt.clf()
plt.cla()