Python create if elif in __init__ for package and function

I am combining all defined function into a class and use if, elif to operate.
I will explain in the following.

First, I have a 3 types of plot, combo, line, and bar.
I know how to define function separately for these three plot.

Second, I want to combine these 3 plots together within a package using if.
The code I tried is:

import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt


class AP(object):

    def __init__(self, dt, date, group, value, value2, value3, value4, value5, value6, TYPE):
        self.dt = dt
        self.date = date
        self.group= carrier
        self.value = value
        self.col1 = col1
        self.col2 = col2
        self.col3 = col3
        self.col4 = col4
        self.TYPE = TYPE

    if self.TYPE == "combo":

        def ComboChart(self, dt, date, group, value, TYPE):
            dataset = pd.read_csv(dt)
            dataset['date'] = pd.to_datetime(dataset[date])
            dataset['yq'] = pd.PeriodIndex(dataset['date'], freq='Q')
            dataset['qtr'] = dataset['date'].dt.quarter
            dataset = dataset.groupby([carrier, 'yq', 'qtr'])[value].sum().reset_index()
            dataset['total.YQGR'] = dataset[value] / dataset.groupby(['qtr', carrier])[value].transform('shift') - 1
            dataset = dataset[np.isfinite(dataset['total.YQGR'])]
            dataset['total.R'] = dataset[value] / dataset.groupby(group)[value].transform('first')
            dataset.yq = dataset.yq.astype(str)

            fig, ax1 = plt.subplots(figsize=(12,7))
            ax2=ax1.twinx()
            sns.lineplot(x='yq',y='total.R', data=dataset, hue=group, ax=ax1, legend = None, palette = ('navy', 'r'), linewidth=5)
            ax1.set_xticklabels(ax1.get_xticks(), rotation=45, fontsize=15, weight = 'heavy')
            ax1.set_xlabel("", fontsize=15)
            ax1.set_ylabel("")
            ax1.set_ylim((0, max(dataset['total.R']) + 0.05))
            sns.barplot(x='yq', y='total.YQGR', data=dataset, hue=group, ax=ax2, palette = ('navy', 'r'))
            ax2.set_yticklabels(['{:.1f}%'.format(a*100) for a in ax2.get_yticks()])
            ax2.set_ylabel("")
            ax2.set_ylim((min(dataset['total.YQGR']) - 0.01, max(dataset['total.YQGR']) + 0.2))
            ax2.get_legend().remove()
            ax2.legend(bbox_to_anchor=(-0.35, 0.5), loc=2, borderaxespad=0., fontsize = 'xx-large')
            for groups in ax2.containers:
                for bar in groups:
                    if bar.get_height() >= 0:
                        ax2.text(
                                bar.get_xy()[0] + bar.get_width()/1.5,
                                bar.get_height() + 0.003, 
                                '{:.1f}%'.format(round(100*bar.get_height(),2)), 
                                color='black',
                                horizontalalignment='center',
                                fontsize = 12, weight = 'heavy'
                                )
                    else:
                        ax2.text(
                                bar.get_xy()[0] + bar.get_width()/1.5,
                                bar.get_height() - 0.008, 
                                '{:.1f}%'.format(round(100*bar.get_height(),2)), 
                                color='black',
                                horizontalalignment='center',
                                fontsize = 12, weight = 'heavy'
                                )
            ax1.yaxis.set_visible(False)
            ax2.yaxis.set_visible(False)
            ax2.xaxis.set_visible(False)
            ax1.spines["right"].set_visible(False)
            ax1.spines["left"].set_visible(False)
            ax1.spines["top"].set_visible(False)
            ax1.spines["bottom"].set_visible(False)
            ax2.spines["right"].set_visible(False)
            ax2.spines["left"].set_visible(False)
            ax2.spines["top"].set_visible(False)
            ax2.spines["bottom"].set_visible(False)
            ax1.set_title(TYPE, fontsize=20)
            plt.show()

            fig.savefig(TYPE, bbox_inches='tight', dpi=600)

    elif self.TYPE == "line":

        def line(self, dt, date, carrier, value, value2, TYPE):
            dataset = pd.read_csv(dt)
            dataset['date'] = pd.to_datetime(dataset[date])
            dataset['yq'] = pd.PeriodIndex(dataset['date'], freq='Q')
            dataset = dataset.groupby([group, 'yq'])[value, value2].sum().reset_index()
            dataset['Arate'] = dataset[value2] / dataset[value]
            dataset.yq = dataset.yq.astype(str)

            fig, ax1 = plt.subplots(figsize=(12,7))
            sns.lineplot(x='yq', y='Arate', data=dataset, hue=group, ax=ax1, linewidth=5)
            ax1.set_xticklabels(dataset['yq'], rotation=45, fontsize = 15)
            ax1.set_xlabel("")
            ax1.set_ylabel("")
            ax1.set_ylim((min(dataset['Arate']) - 0.05, max(dataset['Arate]) + 0.05))
            ax1.set_yticklabels(['{:.1f}%'.format(a*100) for a in ax1.get_yticks()], fontsize = 18, weight = 'heavy')
            ax1.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=2, borderaxespad=0., ncol = 6)
            ax1.yaxis.grid(True)
            ax1.spines["right"].set_visible(False)
            ax1.spines["left"].set_visible(False)
            ax1.spines["top"].set_visible(False)
            ax1.spines["bottom"].set_visible(False)
            ax1.set_title(TYPE, fontsize = 20)
            plt.show()

            fig.savefig(TYPE, bbox_inches='tight', dpi=600)

    elif self.TYPE == "bar":

        def Bar(self, dt, date, group, value3, value4, value5, value6, TYPE):
            dataset = pd.read_csv(dt, sep = '|')
            dataset['date'] = pd.to_datetime(dataset[date])
            dataset['yq'] = pd.PeriodIndex(dataset['date'], freq='Q')
            dataset = dataset.groupby([group, 'yq'])[value3, value4, value5, value6].sum().reset_index()
            dataset = dataset.groupby([group]).tail(4)
            dataset.yq = dataset.yq.astype(str)
            dataset = pd.melt(dataset, id_vars = [group, 'yq'], value_vars = [value3, value4, value5, value6])
            dataset = dataset.groupby(['variable', group]).value.sum().reset_index()
            dataset['L4Qtr'] = dataset.value / dataset.groupby([group]).value.transform('sum')

            fig, ax1 = plt.subplots(figsize=(12,7))
            sns.barplot(x='variable', y='L4Qtr', data=dataset, hue=group, ax=ax1)
            ax1.set_xticklabels(ax1.get_xticklabels(), fontsize=17.5, weight = 'heavy')
            ax1.set_xlabel("", fontsize=15)
            ax1.set_ylabel("")
            ax1.yaxis.set_ticks(np.arange(0, max(dataset['L4Qtr']) + 0.1, 0.05), False)
            ax1.set_yticklabels(['{:.1f}%'.format(a*100) for a in ax1.get_yticks()], fontsize = 18, weight = 'heavy')
            ax1.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=2, borderaxespad=0., ncol = 6)
            for groups in ax1.containers:
                for bar in groups:
                    ax1.text(
                            bar.get_xy()[0] + bar.get_width()/2,
                            bar.get_height() + 0.005, 
                            '{:.1f}%'.format(round(100*bar.get_height(),2)), 
                            color=bar.get_facecolor(),
                            horizontalalignment='center',
                            fontsize = 16, weight = 'heavy'
                                )
            ax1.spines["right"].set_visible(False)
            ax1.spines["left"].set_visible(False)
            ax1.spines["top"].set_visible(False)
            ax1.spines["bottom"].set_visible(False)
            ax1.set_title(TYPE, fontsize=20)
            plt.show()

            fig.savefig(TYPE, bbox_inches='tight', dpi=600)

Third, I hope others can simply use this module as below:

import sys
sys.path.append(r'\\users\desktop\module')
from AP import AP as ap

Finally, when someone assign TYPE, it will automatically plot and save it.

# This will plot combo chart
ap(r'\\users\desktop\dataset.csv', date = 'DATEVALUE', group = 'GRPS', value = 'total', TYPE = 'combo')

Above is the ideal thought. I do not need to pass value2 ~ value6 in it since combo does not use them.
When I want bar:

# This will plot bar chart
ap(r'\\users\desktop\dataset.csv', date = 'DATEVALUE', group = 'GRPS', value3 = 'col1', value4 = 'col2', value5 = 'col3', value6 = 'col4', TYPE = 'combo')

My code is incorrect since error happened. It seems that I need to pass all parameters in it.

However, even I passed all parameters in it. No error but no output.

Any suggestion?