Jupyter "TypeError: invalid type comparison" - pandas

Question

Alright, just started a new job and i have been tasked with writing a simple notebook in jupyter. I really want to impress my supervisor and have been working on this code for hours and can't get it to work, hopefully somebody here can help me.
Here is the code I have been working on:
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import seaborn as sns
df = pd.read_csv(r'C:\Users\jk2588\Documents\EDA\EDA Practice\top1000_dataset.csv', converters={'GENDER': lambda x: int(x == 'Male')}, usecols = ['MEMBER_ID', 'GENDER', 'Age', 'Dement'])
df_gp_1 = df[['MEMBER_ID', 'Dement']].groupby('MEMBER_ID').agg(np.mean).reset_index()
df_gp_2 = df[['MEMBER_ID', 'GENDER', 'Age']].groupby('MEMBER_ID').agg(max).reset_index()
df_gp = pd.merge(df_gp_1, df_gp_2, on = ['MEMBER_ID'])
df.head()
Output: MEMBER_ID Age Dement GENDER
0 000000002 01 36 NaN 0
1 000000002 01 36 NaN 0
2 000000002 01 36 NaN 0
3 000000002 01 36 NaN 0
4 000000002 01 36 NaN 0
df['Dement'] = df['Dement'].fillna(0)
df['Dement'] = df['Dement'].astype('int64')
df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 999 entries, 0 to 998
Data columns (total 4 columns):
MEMBER_ID 999 non-null object
Age 999 non-null int64
Dement 999 non-null int64
GENDER 999 non-null int64
dtypes: int64(3), object(1)
memory usage: 31.3+ KB
freq = ((df_gp.Age.value_counts(normalize = True).reset_index().sort_values(by = 'index').Age)*100).tolist()
number_gp = 7
def ax_settings(ax, var_name, x_min, x_max):
ax.set_xlim(x_min,x_max)
ax.set_yticks([])
ax.spines['left'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.spines['bottom'].set_edgecolor('#444444')
ax.spines['bottom'].set_linewidth(2)
ax.text(0.02, 0.05, var_name, fontsize=17, fontweight="bold", transform = ax.transAxes)
return None
fig = plt.figure(figsize=(12,7))
gs = gridspec.GridSpec(nrows=number_gp,
ncols=2,
figure=fig,
width_ratios= [3, 1],
height_ratios= [1]*number_gp,
wspace=0.2, hspace=0.05
)
ax = [None]*(number_gp + 1)
features = ['0-17', '18-25', '26-35', '36-45', '46-50', '51-55', '55+']
for i in range(number_gp):
ax[i] = fig.add_subplot(gs[i, 0])
ax_settings(ax[i], 'Age: ' + str(features[i]), -1000, 20000)
sns.kdeplot(data=df_gp[(df_gp.GENDER == 'M') & (df_gp.Age == features[i])].Dement, ax=ax[i], shade=True, color="blue", bw=300, legend=False)
sns.kdeplot(data=df_gp[(df_gp.GENDER == 'F') & (df_gp.Age == features[i])].Dement, ax=ax[i], shade=True, color="red", bw=300, legend=False)
if i < (number_gp - 1): ax[i].set_xticks([])
ax[0].legend(['Male', 'Female'], facecolor='w')
ax[number_gp] = fig.add_subplot(gs[:, 1])
ax[number_gp].spines['right'].set_visible(False)
ax[number_gp].spines['top'].set_visible(False)
ax[number_gp].barh(features, freq, color='#004c99', height=0.4)
ax[number_gp].set_xlim(0,100)
ax[number_gp].invert_yaxis()
ax[number_gp].text(1.09, -0.04, '(%)', fontsize=10, transform = ax[number_gp].transAxes)
ax[number_gp].tick_params(axis='y', labelsize = 14)
plt.show()
I am then met with:
C:\Users\jk2588\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\ops.py:1167: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
result = method(y)
--------------------------------------------------------------------------
TypeError Traceback (most recent call last
<ipython-input-38-8665030edb1c> in <module>()
24 ax[i] = fig.add_subplot(gs[i, 0])
25 ax_settings(ax[i], 'Age: ' + str(features[i]), -1000, 20000)
---> 26 sns.kdeplot(data=df_gp[(df_gp.GENDER == 'M') & (df_gp.Age == features[i])].Dement, ax=ax[i], shade=True, color="blue", bw=300, legend=False)
27 sns.kdeplot(data=df_gp[(df_gp.GENDER == 'F') & (df_gp.Age == features[i])].Dement, ax=ax[i], shade=True, color="red", bw=300, legend=False)
28 if i < (number_gp - 1): ax[i].set_xticks([])
~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\ops.py in wrapper(self, other, axis)
1281
1282 with np.errstate(all='ignore'):
-> 1283 res = na_op(values, other)
1284 if is_scalar(res):
1285 raise TypeError('Could not compare {typ} type with Series'
~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\ops.py in na_op(x, y)
1167 result = method(y)
1168 if result is NotImplemented:
-> 1169 raise TypeError("invalid type comparison")
1170 else:
1171 result = op(x, y)
TypeError: invalid type comparison
Please help, i have been faced with an absurd amount of errors this week