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352 lines
11 KiB
Python
352 lines
11 KiB
Python
from datetime import datetime
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import csv
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import gzip
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import json
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import os
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from flask.ext.appbuilder import Base
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import pandas as pd
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from sqlalchemy import Column, String, DateTime, Table, Integer
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from panoramix import app, db, models
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config = app.config
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DATA_FOLDER = os.path.join(config.get("BASE_DIR"), 'data')
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def get_or_create_db(session):
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print("Creating database reference")
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DB = models.Database
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dbobj = session.query(DB).filter_by(database_name='main').first()
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if not dbobj:
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dbobj = DB(database_name="main")
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print(config.get("SQLALCHEMY_DATABASE_URI"))
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dbobj.sqlalchemy_uri = config.get("SQLALCHEMY_DATABASE_URI")
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session.add(dbobj)
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session.commit()
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return dbobj
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def load_world_bank_health_n_pop():
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"""
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Details on how the data was loaded from
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http://data.worldbank.org/data-catalog/health-nutrition-and-population-statistics
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DIR = ""
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df_country = pd.read_csv(DIR + '/HNP_Country.csv')
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df_country.columns = ['country_code'] + list(df_country.columns[1:])
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df_country = df_country[['country_code', 'Region']]
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df_country.columns = ['country_code', 'region']
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df = pd.read_csv(DIR + '/HNP_Data.csv')
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del df['Unnamed: 60']
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df.columns = ['country_name', 'country_code'] + list(df.columns[2:])
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ndf = df.merge(df_country, how='inner')
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dims = ('country_name', 'country_code', 'region')
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vv = [str(i) for i in range(1960, 2015)]
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mdf = pd.melt(ndf, id_vars=dims + ('Indicator Code',), value_vars=vv)
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mdf['year'] = mdf.variable + '-01-01'
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dims = dims + ('year',)
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pdf = mdf.pivot_table(values='value', columns='Indicator Code', index=dims)
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pdf = pdf.reset_index()
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pdf.to_csv(DIR + '/countries.csv')
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pdf.to_json(DIR + '/countries.json', orient='records')
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"""
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tbl = 'wb_health_population'
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with gzip.open(os.path.join(DATA_FOLDER, 'countries.json.gz')) as f:
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pdf = pd.read_json(f)
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pdf.year = pd.to_datetime(pdf.year)
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pdf.to_sql(
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tbl,
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db.engine,
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if_exists='replace',
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chunksize=500,
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dtype={
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'year': DateTime(),
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'country_code': String(3),
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'country_name': String(255),
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'region': String(255),
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},
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index=False)
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print("Creating table reference")
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TBL = models.SqlaTable
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obj = db.session.query(TBL).filter_by(table_name=tbl).first()
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if not obj:
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obj = TBL(table_name='wb_health_population')
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obj.main_dttm_col = 'year'
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obj.database = get_or_create_db(db.session)
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models.Table
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db.session.add(obj)
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db.session.commit()
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obj.fetch_metadata()
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def load_birth_names():
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session = db.session
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with gzip.open(os.path.join(DATA_FOLDER, 'birth_names.json.gz')) as f:
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pdf = pd.read_json(f)
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pdf.ds = pd.to_datetime(pdf.ds, unit='ms')
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pdf.to_sql(
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'birth_names',
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db.engine,
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if_exists='replace',
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chunksize=500,
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dtype={
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'ds': DateTime,
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'gender': String(16),
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'state': String(10),
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'name': String(255),
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},
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index=False)
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l = []
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print("Done loading table!")
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print("-" * 80)
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print("Creating table reference")
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TBL = models.SqlaTable
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obj = db.session.query(TBL).filter_by(table_name='birth_names').first()
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if not obj:
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obj = TBL(table_name = 'birth_names')
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obj.main_dttm_col = 'ds'
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obj.database = get_or_create_db(db.session)
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models.Table
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db.session.add(obj)
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db.session.commit()
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obj.fetch_metadata()
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tbl = obj
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print("Creating some slices")
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def get_slice_json(slice_name, **kwargs):
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defaults = {
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"compare_lag": "10",
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"compare_suffix": "o10Y",
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"datasource_id": "1",
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"datasource_name": "birth_names",
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"datasource_type": "table",
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"limit": "25",
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"flt_col_1": "gender",
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"flt_eq_1": "",
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"flt_op_1": "in",
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"granularity": "ds",
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"groupby": [],
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"metric": 'sum__num',
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"metrics": ["sum__num"],
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"row_limit": config.get("ROW_LIMIT"),
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"since": "100 years",
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"slice_name": slice_name,
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"until": "now",
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"viz_type": "table",
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"where": "",
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"markup_type": "markdown",
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}
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d = defaults.copy()
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d.update(kwargs)
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return json.dumps(d, indent=4, sort_keys=True)
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Slice = models.Slice
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slices = []
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slice_name = "Girls"
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slc = db.session.query(Slice).filter_by(slice_name=slice_name).first()
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if not slc:
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slc = Slice(
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slice_name=slice_name,
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viz_type='table',
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datasource_type='table',
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table=tbl,
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params=get_slice_json(
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slice_name, groupby=['name'], flt_eq_1="girl", row_limit=50))
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session.add(slc)
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slices.append(slc)
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slice_name = "Boys"
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slc = session.query(Slice).filter_by(slice_name=slice_name).first()
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if not slc:
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slc = Slice(
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slice_name=slice_name,
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viz_type='table',
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datasource_type='table',
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table=tbl,
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params=get_slice_json(
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slice_name, groupby=['name'], flt_eq_1="boy", row_limit=50))
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session.add(slc)
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slices.append(slc)
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slice_name = "Participants"
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slc = session.query(Slice).filter_by(slice_name=slice_name).first()
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if not slc:
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slc = Slice(
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slice_name=slice_name,
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viz_type='big_number',
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datasource_type='table',
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table=tbl,
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params=get_slice_json(
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slice_name, viz_type="big_number", granularity="ds",
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compare_lag="5", compare_suffix="over 5Y"))
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session.add(slc)
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slices.append(slc)
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slice_name = "Genders"
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slc = session.query(Slice).filter_by(slice_name=slice_name).first()
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if not slc:
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slc = Slice(
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slice_name=slice_name,
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viz_type='pie',
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datasource_type='table',
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table=tbl,
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params=get_slice_json(
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slice_name, viz_type="pie", groupby=['gender']))
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session.add(slc)
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slices.append(slc)
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slice_name = "Gender by State"
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slc = session.query(Slice).filter_by(slice_name=slice_name).first()
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if not slc:
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slc = Slice(
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slice_name=slice_name,
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viz_type='dist_bar',
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datasource_type='table',
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table=tbl,
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params=get_slice_json(
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slice_name, flt_eq_1="other", viz_type="dist_bar",
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metrics=['sum__sum_girls', 'sum__sum_boys'],
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groupby=['state'], flt_op_1='not in', flt_col_1='state'))
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session.add(slc)
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slices.append(slc)
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slice_name = "Trends"
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slc = session.query(Slice).filter_by(slice_name=slice_name).first()
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if not slc:
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slc = Slice(
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slice_name=slice_name,
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viz_type='line',
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datasource_type='table',
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table=tbl,
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params=get_slice_json(
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slice_name, viz_type="line", groupby=['name'],
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granularity='ds', rich_tooltip='y', show_legend='y'))
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session.add(slc)
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slices.append(slc)
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slice_name = "Title"
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slc = session.query(Slice).filter_by(slice_name=slice_name).first()
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code = """
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### Birth Names Dashboard
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The source dataset came from [here](https://github.com/hadley/babynames)
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"""
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if not slc:
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slc = Slice(
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slice_name=slice_name,
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viz_type='markup',
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datasource_type='table',
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table=tbl,
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params=get_slice_json(
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slice_name, viz_type="markup", markup_type="markdown",
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code=code))
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session.add(slc)
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slices.append(slc)
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slice_name = "Name Cloud"
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slc = session.query(Slice).filter_by(slice_name=slice_name).first()
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if not slc:
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slc = Slice(
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slice_name=slice_name,
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viz_type='word_cloud',
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datasource_type='table',
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table=tbl,
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params=get_slice_json(
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slice_name, viz_type="word_cloud", size_from="10",
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series='name', size_to="70", rotation="square",
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limit='100'))
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session.add(slc)
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slices.append(slc)
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slice_name = "Pivot Table"
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slc = session.query(Slice).filter_by(slice_name=slice_name).first()
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if not slc:
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slc = Slice(
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slice_name=slice_name,
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viz_type='pivot_table',
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datasource_type='table',
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table=tbl,
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params=get_slice_json(
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slice_name, viz_type="pivot_table", metrics=['sum__num'],
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groupby=['name'], columns=['state']))
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session.add(slc)
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slices.append(slc)
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print("Creating a dashboard")
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Dash = models.Dashboard
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dash = session.query(Dash).filter_by(dashboard_title="Births").first()
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if not dash:
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dash = Dash(
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dashboard_title="Births",
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position_json="""
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[
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{
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"size_y": 4,
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"size_x": 2,
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"col": 3,
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"slice_id": "1",
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"row": 3
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},
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{
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"size_y": 4,
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"size_x": 2,
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"col": 1,
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"slice_id": "2",
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"row": 3
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},
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{
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"size_y": 2,
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"size_x": 2,
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"col": 1,
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"slice_id": "3",
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"row": 1
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},
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{
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"size_y": 2,
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"size_x": 2,
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"col": 3,
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"slice_id": "4",
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"row": 1
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},
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{
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"size_y": 3,
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"size_x": 7,
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"col": 5,
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"slice_id": "5",
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"row": 4
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},
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{
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"size_y": 5,
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"size_x": 11,
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"col": 1,
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"slice_id": "6",
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"row": 7
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},
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{
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"size_y": 3,
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"size_x": 3,
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"col": 9,
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"slice_id": "7",
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"row": 1
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},
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{
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"size_y": 3,
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"size_x": 4,
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"col": 5,
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"slice_id": "8",
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"row": 1
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}
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]
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"""
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)
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session.add(dash)
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for s in slices:
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dash.slices.append(s)
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session.commit()
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