示例#1
0
def generatePurchasePlot(params, df):
    print('bar plot entered')

    ### GENERATE PLOTS ###

    x = params.get('x')
    y = params.get('y')
    hue = params.get('hue')
    IMG_PATH = os.path.join(IMG_ROOT_PATH,
                            str(x) + str(y) + str(hue) + '_bar.jpg')

    if os.path.isfile(IMG_PATH) != True:
        barPlot(x, y, hue, IMG_PATH, df)


### GENERATE HTML SCRIPT ###
    if hue == '':
        comment = f'{y} fordelt over {x}'
    else:
        comment = f'{y} fordelt over {x}, kategorisert i {hue}'

    gen_HTML_report(header='Gruppering plot',
                    sub_header=comment,
                    IMG_PATH=IMG_PATH)

    ### RETURN BASICARD RESPONSE ###

    print('bar plot entered')
    return basiCard(msg=comment, title='Report', url=URL_REPORT)
示例#2
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def generateCountPlot(params, df):

    ### GENERATE PLOTS ###
    gruppe = params.get('gruppe')
    hue = params.get('hue')

    IMG_PATH = os.path.join(IMG_ROOT_PATH,
                            str(gruppe) + str(hue) + '_count.jpg')
    if os.path.isfile(IMG_PATH) != True:
        countPlot(gruppe, hue, IMG_PATH, df)

    if hue != '':
        comment = f'Antall transaksjoner fordelt i {gruppe}, kategorisert i {hue}'
    else:
        comment = f'Antall transaksjoner fordelt i {gruppe}'


### GENERATE HTML SCRIPT ###

    gen_HTML_report(header='Gruppering plot',
                    sub_header=comment,
                    IMG_PATH=IMG_PATH)

    ### RETURN BASICARD RESPONSE ###

    return basiCard(msg=comment, title='Report', url=URL_REPORT)
示例#3
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def generateCorr(params, df):

    IMG_PATH = os.path.join(IMG_ROOT_PATH, 'korrelasjon.jpg')

    if os.path.isfile(IMG_PATH) != True:

        df_pred = pd.read_csv(os.path.join('data', 'BFCleaned.csv'),
                              index_col=0)
        df_pred['Alder'] = df_pred['Alder'].map({
            '0-17': 0,
            '18-25': 1,
            '26-35': 2,
            '36-45': 3,
            '46-50': 4,
            '51-55': 5,
            '55+': 6
        })
        df_pred['Kjønn'] = df_pred['Kjønn'].map({'M': 0, 'F': 1})
        df_pred['By'] = df_pred['By'].map({'A': 0, 'B': 1, 'C': 2})
        df_pred['Boperiode_i_by'] = df_pred['Boperiode_i_by'].map({
            '0': 0,
            '1': 1,
            '2': 2,
            '3': 3,
            '4+': 4
        })

        import seaborn as sns
        corrmat = df_pred[[
            'Kjønn', 'Alder', 'Yrke', 'By', 'Boperiode_i_by', 'Sivilstatus',
            'Produkt_kategori', 'Salg'
        ]].corr()
        fig, ax = plt.subplots(figsize=(10, 6))
        sns.heatmap(corrmat, vmax=.8, square=True)

        plt.savefig(IMG_PATH)

    gen_HTML_report(header='Korrelasjonsmatrise',
                    sub_header='',
                    IMG_PATH=IMG_PATH)

    ### RETURN BASICARD RESPONSE ###

    return basiCard(msg='Korrelasjonsmatrise', title='Report', url=URL_REPORT)
示例#4
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def generateKakePlot(params, df):
    ### GENERATE PLOTS ###

    gruppe = params.get('gruppe')
    IMG_PATH = os.path.join(IMG_ROOT_PATH, str(gruppe) + '_kake.jpg')

    if os.path.isfile(IMG_PATH) != True:
        kakePlot(gruppe, IMG_PATH, df)


### GENERATE HTML SCRIPT ###

    gen_HTML_report(header='Gruppering plot',
                    sub_header=f'Antall transaksjoner fordelt i {gruppe}',
                    IMG_PATH=IMG_PATH)

    ### RETURN BASICARD RESPONSE ###

    return basiCard(msg=f'Antall transaksjoner fordelt i {gruppe}',
                    title='Report',
                    url=URL_REPORT)