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k = hs.hotkey.modal.new('ctrl-shift', 'n')
function k:entered() hs.alert'Virtual Numpad' end
function k:exited() hs.alert'Exit Virtual Numpad' end
k:bind('ctrl-shift', 'n', function() k:exit() end)

hs.fnutils.each({
  { key='j', padkey='pad1'},
  { key='k', padkey='pad2'},
  { key='l', padkey='pad3'},
  { key='u', padkey='pad4'},

c-l-nguyen

import pandas as pd

df = pd.read_csv("Global Temperature Anomalies.csv")
print(df.columns)

# parameter values
id_vars = ['Hemisphere', 'Year']
cols_to_pivot = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul',
       'Aug', 'Sep', 'Oct', 'Nov', 'Dec', 'J-D', 'D-N', 'DJF', 'MAM', 'JJA',
       'SON']

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# append all DataFrames into one before writing to single table in Hyper
final_df = df1.append(df2).append(df3).reset_index(drop=True)
pantab.frames_to_hyper({"pokemon": final_df}, "hyper/all_pokemon_in_one.hyper")

# this produces the same result as above
pantab.frame_to_hyper(df1, "hyper/all_pokemon_append.hyper", table = "pokemon")
pantab.frame_to_hyper(df2, "hyper/all_pokemon_append.hyper", table = "pokemon", table_mode = "a")
pantab.frame_to_hyper(df3, "hyper/all_pokemon_append.hyper", table = "pokemon", table_mode = "a")

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print(pantab.frames_from_hyper("hyper/pokemon_public.hyper").keys())
# dict_keys([TableName('public', 'pokemon')])

print(pantab.frames_from_hyper("hyper/pokemon_extract.hyper").keys())
# dict_keys([TableName('Extract', 'pokemon')])

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# this errors out with message "HyperException: Specified table does not exist: pokemon."
pantab.frame_from_hyper("hyper/pokemon_extract.hyper", table = "pokemon")

# need to specify schema to read table from
pantab.frame_from_hyper("hyper/pokemon_extract.hyper", table = TableName("Extract", "pokemon"))

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# these two are equivalent
pantab.frame_from_hyper("hyper/pokemon_public.hyper", table = "pokemon")
pantab.frame_from_hyper("hyper/pokemon_public.hyper", table = TableName("public", "pokemon"))

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import pandas as pd
import pantab
from tableauhyperapi import TableName

df = pd.read_csv("data/starter_pokemon_grass.csv")

# save DataFrame output to .hyper file
pantab.frame_to_hyper(df, "hyper/pokemon_public.hyper", table = "pokemon")

# save to schema other than public

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df1 = pd.read_csv("data/starter_pokemon_grass.csv")
df2 = pd.read_csv("data/starter_pokemon_fire.csv")
df3 = pd.read_csv("data/starter_pokemon_water.csv")

dict_df = {"grass": df1, "fire": df2, "water": df3}

pantab.frames_to_hyper(dict_df, "hyper/all_pokemon_separate.hyper")

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import csv
from tableauhyperapi import HyperProcess, Telemetry, Connection, CreateMode, NOT_NULLABLE, NULLABLE, SqlType, \
TableDefinition, Inserter, escape_name, escape_string_literal, HyperException, TableName

with HyperProcess(telemetry=Telemetry.DO_NOT_SEND_USAGE_DATA_TO_TABLEAU) as hyper:
    print("starting up Hyper Process")
    with Connection(hyper.endpoint, 'hyper/pokemon_hyper_api.hyper', CreateMode.CREATE_AND_REPLACE) as connection:
        print("creating or replacing pokemon_hyper_api.hyper")
        
        poke_table = TableDefinition(TableName('public','pokemon'), [