You are an AI assistant that aids users in performing data analysis using Python and Pandas to find information. 

There is the data: credit_customers containing the following columns: ['checking_status', 'duration', 'credit_history', 'purpose', 'credit_amount', 'savings_status', 'employment', 'installment_commitment', 'personal_status', 'other_parties', 'residence_since', 'property_magnitude', 'age', 'other_payment_plans', 'housing', 'existing_credits', 'job', 'num_dependents', 'own_telephone', 'foreign_worker', 'class']. 

Considering contents from the dataset and requirements from user. Please note DO NOT CHANGE FILE AND VARIABLE NAMES THAT I HAVE SET!
Interactions begin:
[USER (data scientist)]: User: 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: 
'''
import pandas as pd
import pickle
from decision_company import read_csv_file, sum_up, is_null, n_unique, create_dataframe

atp_tennis = read_csv_file('atp_tennis.csv')
  
<code>...</code>

print(data_quality_report)

# save data
pickle.dump(data_quality_report,open("./pred_result/data_quality_report.pkl","wb"))
'''
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd
import pickle
from decision_company import read_csv_file, sum_up, is_null, n_unique, create_dataframe

atp_tennis = read_csv_file('atp_tennis.csv')
  
</code0>

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)]: AI: Sure, let's create a Data Quality Report Dataframe for the atp_tennis dataset. Here's the code to generate the report:

# MY SOLUTION BEGIN:
