day of the week as X in Seaborn plot - python-3.x

Question

I have a dataset with clicks and impressions, I aggregated them by the day of week using groupby and agg
df2=df.groupby('day_of_week',as_index=False, sort=True, group_keys=True).agg({'Clicks':'sum','Impressions':'sum'})
Then I was trying to plot them out using subplot
f, axes = plt.subplots(2, 2, figsize=(7, 7))
sns.countplot(data=df2['Clicks'], x=df2['day_of_week'],ax=axes[0, 0])
sns.countplot(data=df2["Impressions"], x=df2['day_of_week'],ax=axes[0, 1])
but instead using the day of week as the X, the plot used values in clicks and impressions instead. Is there a way to force the X to day of the week while value is in Y instead? Thanks.
Full code
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style("whitegrid")
df=pd.read_csv('data/data_clean.csv')
df2=df.groupby('day_of_week',as_index=False, sort=True, group_keys=True).agg({'Clicks':'sum','Impressions':'sum'})
f, axes = plt.subplots(2, 2, figsize=(7, 7))
sns.countplot(data=df2['Clicks'], x=df2['day_of_week'],ax=axes[0, 0])
sns.countplot(data=df2["Impressions"], x=df2['day_of_week'],ax=axes[0, 1])
plt.show()
Fake Data:
day_of_week,Clicks,Impressions
0 100 2000
1 400 4000
2 300 3500
3 200 2000
4 100 1000
5 50 500
6 10 150

Answer 1

I was able to find the answer with seaborn with Peter's guidance.
The correct plotting code is
sns.barplot( x=df2['day_of_week'],y=df2['Clicks'] , color="skyblue", ax=axes[0, 0])
sns.barplot( x=df2['day_of_week'],y=df2['Impressions'] , color="olive", ax=axes[0, 1])
It seems seaborn by default would take the first variable as X instead of Y.

Answer 2

Based on the seaborn docs, I think countplot expects a long-form dataframe such as your df, not the pre-aggregated df2 that you built and pass in your question. countplot does the counting for you.
However, your df2 is ready for a pandas bar plot:
df2.plot(kind='bar', y=['Impressions', 'Clicks'])
Result: