6NTifA69

1import pandas as pd
2import matplotlib.pyplot as plt
3import eia
4
5def retrieve_time_series(api, series_ID):
6    """
7    Return the time series dataframe, based on API and unique Series ID
8    Arguments:
9        api: API that we're connected to
10        series_ID: string. Name of the series that we want to pull from the EIA API
11    Outputs:
12        df: Pandas dataframe of time series
13    """
14    #Retrieve Data By Series ID 
15    series_search = api.data_by_series(series=series_ID)
16    ##Create a pandas dataframe from the retrieved time series
17    df = pd.DataFrame(series_search)
18    return df
19
20def scatterplot(x_data, y_data, x_label, y_label, title):
21    """
22    Arguments:
23        x_data: Series. Desired x-axis for scatterplot.
24        y_data: Series. Desired y-axis for scatterplot.
25        x_label: String. Label for x-axis.
26        y_label: String. Label for y-axis.
27        title: String. Title of plot
28    Outputs:
29        Scatterplot in console.
30    """
31    fig, ax = plt.subplots()
32    ax.scatter(x_data, y_data, s = 30, color = '#539caf', alpha = 0.75)
33    ax.set_title(title)
34    ax.set_xlabel(x_label)
35    ax.set_ylabel(y_label)
36    fig.autofmt_xdate()
37    
38#####EXECUTE IN MAIN BLOCK
39
40#Create EIA API using your specific API key
41api_key = 'YOUR API KEY HERE'
42api = eia.API(api_key)
43    
44#Pull the oil WTI price data
45series_ID='PET.EER_EPMRU_PF4_RGC_DPG.D'
46gasoline_price_df=retrieve_time_series(api, series_ID)
47gasoline_price_df.reset_index(level=0, inplace=True)
48#Rename the columns for easer analysis
49gasoline_price_df.rename(columns={'index':'Date',
50            gasoline_price_df.columns[1]:'Gasoline_Price'}, 
51            inplace=True)
52     
53#Visualize anomalies using matplotlib function
54scatterplot(gasoline_price_df['Date'],
55                gasoline_price_df['Gasoline_Price'], 
56                'Date', 
57                'Gasoline Price (Dollars Per Gallon)', 
58                'US Gulf Coast Gasoline Price Time Series: 2014-Present')