tga_taxes.py

import pandas as pd
import treasury_gov_pandas
from bokeh.plotting import figure, show
from bokeh.models   import NumeralTickFormatter, HoverTool
import bokeh.models

import bokeh.palettes
import bokeh.transform
# ----------------------------------------------------------------------
df = treasury_gov_pandas.update_records(
    url = 'https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/dts/deposits_withdrawals_operating_cash')

df['record_date'] = pd.to_datetime(df['record_date'])

df['transaction_today_amt'] = pd.to_numeric(df['transaction_today_amt'])

# ----------------------------------------------------------------------
def show_concise(df):
    return df.drop(columns=['table_nbr', 'table_nm', 'src_line_nbr', 'record_fiscal_year', 'record_fiscal_quarter', 'record_calendar_year', 'record_calendar_quarter', 'record_calendar_month', 'record_calendar_day'])

tmp = df[(df['transaction_type'] == 'Deposits') &   ((df['transaction_catg'].str.contains('Tax'))   |   (df['transaction_catg'].str.contains('FTD')))   ]

# show_concise(tmp)

# print(show_concise(tmp).tail(500).to_string())

# tmp.value_counts('transaction_catg')
# ----------------------------------------------------------------------
p = figure(
    title='TGA Taxes',
    sizing_mode='stretch_both', 
    x_axis_type='datetime', 
    x_axis_label='record_date', 
    y_axis_label='amt')

p.add_tools(HoverTool(tooltips=[
    ('record_date',    '@record_date{%F}'),
    ('transaction_today_amt', '@transaction_today_amt{$0.0a}'),
    ('transaction_type', '@transaction_type'),
    ('transaction_catg', '@transaction_catg'),
    ('transaction_desc', '@transaction_desc'),   
    ],

    formatters={ '@record_date' : 'datetime' }
        
    ))

width = pd.Timedelta(days=0.5)

colors = bokeh.palettes.Category20[20]

color_index = 0

for transaction_catg in tmp['transaction_catg'].unique():
    items = tmp[tmp['transaction_catg'] == transaction_catg]
    # p.line(  x='record_date',   y='transaction_today_amt',  legend_label=transaction_catg, source=bokeh.models.ColumnDataSource(items))
    p.vbar(  x='record_date',   top='transaction_today_amt',  legend_label=transaction_catg, source=bokeh.models.ColumnDataSource(items), width=width, color=colors[color_index])
    color_index = (color_index + 1) % len(colors)

p.xaxis.ticker = bokeh.models.DatetimeTicker(desired_num_ticks=30)

p.legend.click_policy = 'hide'

p.legend.location = 'top_left'

show(p)