AHT20 average_date, get_entries, plot_data methods

aht20-step-4.py

def average_date(date, entries):
    # Get a list of all entries for this date
    events = list(filter(lambda x: (x['date'][0:10] == date), entries))
    return {
        'date': pd.to_datetime(date),
        'temperature': sum(float(e['temperature']) for e in events) / len(events),
        'humidity': sum(float(e['humidity']) for e in events) / len(events)
    }

# Returns entries as DataFrames
def get_entries(location):
    # load entries from file
    with open("entries.json", "r") as f:
        all_entries = json.loads(f.read())

    # Filter entries by our location
    entries = list(filter(lambda e: e['location'] == location, all_entries))

    # Ensure at least one entry is returned for this location
    if len(entries) == 0:
        print('Error: No entries found for location ({}). Try another?'.format(location))
        sys.exit(1)

    # Get a set/list of unique dates in YYYY-MM-DD format from the entries
    dates = set(map(lambda e: e['date'][0:10], entries))

    # Get the average temperature and humidity per day and convert to a DataFrame
    df = pd.DataFrame(map(lambda date: average_date(date, entries), dates))

    # Sort values by the date and set it as the index
    df = df.sort_values('date', ascending=True).set_index('date')

    # Use the same DF for both, but rename the subject field as needed
    return {
        'temperature': df.rename(columns={'temperature': 'value'}),
        'humidity': df.rename(columns={'humidity': 'value'})
    }

# Plot dataset on a axis with it's display information
def plot_data(data, ax, x_label, y_label, color, alpha = 1):
    color = 'tab:{}'.format(color)

    # Set labels
    ax.set_xlabel(x_label)
    ax.set_ylabel(y_label, color=color)
    ax.tick_params(axis='y', labelcolor=color)

    # Plot data
    ax.plot(data.index, data.value, marker='o', color=color, alpha=alpha)