[USER (data scientist)]: Hi, let's start by assessing the data quality of the atp_tennis dataset. To achieve this, we'll create a Data Quality Report DataFrame that covers two main aspects: a list of columns along with the number of missing values in each column, A list of unique values for each categorical column, such as Tournament, Series, Court, Surface, and Round. 
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd
import pickle

atp_tennis = pd.read_csv('atp_tennis.csv')

# YOUR SOLUTION BEGIN:
<code1>
[COMPLETE YOUR CODE] 
</code1>
# YOUR SOLUTION END

print(data_quality_report)

# save data
pickle.dump(data_quality_report,open("./pred_result/data_quality_report.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: Sure, let's create a Data Quality Report Dataframe for the atp_tennis dataset. Here's the code to generate the report:
'''
import pandas as pd
import pickle

atp_tennis = pd.read_csv('atp_tennis.csv')

# YOUR SOLUTION BEGIN:
