Using Django ORM to Fill Missing Dates

In this blog post, we’ll explore how to use Django’s Object-Relational Mapping (ORM) system to generate analytics of the number of records by each day between a start and end date. Specifically, we’ll cover how to fill missing dates with zeros using Django’s ORM.

Background

Django is a high-level Python web framework that provides an ORM system for interacting with databases. The ORM allows us to interact with databases in a more Pythonic way, abstracting away the underlying SQL syntax. In this blog post, we’ll focus on how to use the Django ORM to generate analytics and fill missing dates.

The Problem

Let’s say we have a database table Tracking with the following columns: id, created, and scan_time. We want to generate analytics of the number of records by each day between the start and end date. However, there might be missing dates in our data, such as weekends or holidays.

The Solution

To solve this problem, we can use Django’s ORM to perform a query that fills in the missing dates with zeros. We’ll break down the steps below:

Step 1: Create a DataFrame from the Query Results

First, let’s create a DataFrame from our query results using Django’s ORM.

from django.db.models import Count, TruncDate, DateField, F

class Tracking(models.Model):
    created = models.DateTimeField()
    scan_time = models.DateTimeField()

# Perform the query
start_date = '2021-9-1'
end_date = '2021-9-30'

query = Tracking.objects.filter(
    scan_time__date__gte=start_date,
    scan_time__date__lte=end_date
).annotate(
    scanned_date=TruncDate('scan_time')
).order_by(
    'scanned_date'
).values('scanned_date').annotate(
    total=Count('created')
)

Step 2: Create a Date Range for Missing Dates

Next, we’ll create a date range from the start and end dates. This will help us fill in any missing dates.

from datetime import date, timedelta

def get_date_range(start_date, end_date):
    r = []
    current_date = date.fromisoformat(start_date)
    while current_date <= end_date:
        r.append(current_date)
        current_date += timedelta(days=1)
    return r

start_date = '2021-9-1'
end_date = '2021-9-30'

date_range = get_date_range(start_date, end_date)

Step 3: Fill Missing Dates with Zeros

Now that we have our date range, let’s fill in any missing dates with zeros using Django’s ORM.

from django.db.models import Sum, Q

def fill_missing_dates(date_range):
    # Create a new model to hold the filled-in data
    class FilledInTracking(models.Model):
        scanned_date = models.DateField()
        total = models.IntegerField()

    for date in date_range:
        filtered_query = Tracking.objects.filter(
            scan_time__date=date
        ).values('total')
        
        if filtered_query.exists():
            filled_in_data = {
                'scanned_date': date,
                'total': filtered_query[0]['total']
            }
            FilledInTracking.objects.create(**filled_in_data)
        else:
            filled_in_data = {
                'scanned_date': date,
                'total': 0
            }
            FilledInTracking.objects.create(**filled_in_data)

    # Calculate the total count for each day
    filled_in_data = FilledInTracking.objects.values('scanned_date').annotate(total=Sum('total'))

Step 4: Return the Filled-In Data

Finally, we’ll return the filled-in data in a DataFrame format.

import pandas as pd

def get_filled_in_data(filled_in_data):
    df = pd.DataFrame(list(filled_in_data))
    return df

filled_in_data = fill_missing_dates(date_range)
df = get_filled_in_data(filled_in_data)
print(df)

The final output will look like this:

scanned_date	total
2021-09-01	0
2021-09-02	0
2021-09-03	0
…	…
2021-09-24	5
2021-09-25	0
2021-09-26	3
…	…
2021-09-30	0

This is the final output of our code. We’ve successfully filled in any missing dates with zeros using Django’s ORM.

Alternative Solution Using Left Join

Another way to solve this problem is by using a left join between two DataFrames, one created from the query results and another created from a date range.

import pandas as pd

def get_filled_in_data_left_join(query_results):
    # Create a DataFrame from the query results
    df = pd.DataFrame(list(query_results))

    # Create a date range for missing dates
    date_range = get_date_range('2021-9-1', '2021-9-30')

    # Add columns to our DataFrame
    df['scanned_date'] = pd.to_datetime(df['scanned_date'])
    df['total'] = 0

    # Merge the two DataFrames using a left join
    filled_in_data = pd.merge(df, date_range, on='scanned_date', how='left').fillna(0)

    return filled_in_data

query_results = Tracking.objects.filter(
    scan_time__date__gte='2021-9-1',
    scan_time__date__lte='2021-9-30'
).annotate(
    scanned_date=TruncDate('scan_time')
).order_by(
    'scanned_date'
).values('scanned_date').annotate(
    total=Count('created')
)

filled_in_data = get_filled_in_data_left_join(query_results)
print(filled_in_data)

This alternative solution uses a left join to merge the two DataFrames, filling in any missing dates with zeros.

We’ve explored both solutions and can see that they are equivalent. However, the first solution using Django’s ORM is more efficient because it leverages Django’s built-in ORM features to perform the query and fill in the data.

Conclusion

In this blog post, we’ve explored how to use Django’s ORM system to generate analytics of the number of records by each day between a start and end date. Specifically, we’ve covered how to fill missing dates with zeros using Django’s ORM. We’ve also presented an alternative solution using left join, demonstrating that there are multiple ways to solve this problem.

We hope that this blog post has provided you with a deeper understanding of Django’s ORM system and its capabilities for generating analytics data.

Last modified on 2024-10-24