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define([
], function () {
// TEST
/**
* Replaced with
'([a-zA-Z0-9_.]*)'[ ]*: (\{[\n\t ]*id:)[ ]*'([a-zA-Z0-9]*)'
'$3': $2 '$1'
*/
var PANDAS_FUNCTION = {
'pdPdo_series': {
id: 'Series',
name: 'Series',
library: 'pandas',
description: '1 dimension array with same data types',
code: '${o0} = pd.Series(${i0}${v})',
input: [
{
name:'i0',
type:['var', 'list', 'dict'],
label: 'Data'
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to',
component: 'input_single'
}
],
variable: [
{
name:'index',
type:'list',
label: 'Index'
},
{
name:'name',
type:'text',
label:'Series Name'
}
]
},
'pdPdo_dataframe': {
id: 'Dataframe',
name: 'DataFrame',
library: 'pandas',
description: '2 dimension data table type pandas variable',
code: '${o0} = pd.DataFrame(${i0}${v})',
input: [
{
name:'i0',
type:['var', 'list2d', 'dict'],
label: 'Data',
component: 'table'
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name:'index',
type:'list',
label:'Index List'
},
{
name:'columns',
type:'list',
label:'Column List'
}
]
},
'pdPdo_index': {
id: 'Index',
name: 'Index',
library: 'pandas',
description: 'Create index object',
code: '${o0} = pd.Index(${data}${v})',
input: [
{
name: 'data',
type: ['list', 'var'],
label: 'Data'
}
],
variable: [
{
name: 'dtype',
type: 'var',
label: 'Numpy Dtype',
component: 'option_select',
options: ["'object'", 'None', "'int32'", "'int64'", "'float32'", "'float64'", "'string'", "'complex64'", "'bool'"],
default: "'object'"
},
{
name: 'copy',
type: 'bool',
label: 'Copy',
component: 'bool_checkbox',
default: 'False'
},
{
name: 'name',
type: 'var',
label: 'Index Name'
},
{
name: 'tupleize_cols',
type: 'bool',
label: 'Create Multiindex',
default: 'True',
component: 'bool_checkbox'
}
],
output: [
{
name: 'o0',
type: 'var',
label: 'Allocate to'
}
]
},
'pd004': {
id: 'read_csv',
name: 'Read CSV',
library: 'pandas',
description: '',
code: '${o0} = pd.read_csv(${i0}${v}${etc})',
input: [
{
name:'i0',
type:'text',
label: 'File Path',
component: 'file'
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name: 'encoding',
type: 'text',
label: 'Encoding'
},
{
name: 'header',
type: 'int',
label: 'Header',
component: 'option_suggest',
options: ['None', '0']
},
{
name: 'sep',
type: 'text',
label: 'Seperator'
},
{
name: 'names',
type: 'list',
label: 'Columns'
},
{
name: 'usecols',
type: 'list',
label: 'Column List To Use'
},
{
name: 'index_col',
type: 'var',
label: 'Column To Use As Index'
},
{
name: 'na_values',
type: 'list',
label: 'Na Values'
},
{
name: 'skiprows',
type: 'list',
label: 'Rows To Skip'
},
{
name: 'chunksize',
type: 'int',
label: 'Chunksize'
}
]
},
'pd005': {
id: 'to_csv',
name: 'To CSV',
library: 'pandas',
description: 'dataframe to csv',
code: '${i0}.to_csv(${i1}${v}${etc})',
input: [
{
name:'i0',
type:'var',
label: 'DataFrame',
component: 'var_select',
var_type: ['DataFrame', 'Series']
},
{
name:'i1',
type:'text',
label: 'File Path',
component: 'file'
}
],
output: [
],
variable: [
{
name: 'encoding',
type: 'text',
label: 'Encoding'
},
{
name: 'header',
type: ['bool', 'list'],
label: 'Header',
default: 'True',
component: 'bool_checkbox'
},
{
name: 'index',
type: 'bool',
label: 'Index',
default: 'True',
component: 'bool_checkbox'
},
{
name: 'sep',
type: 'text',
label: 'Seperator'
},
{
name: 'na_rep',
type: 'text',
label: 'Na Replacing Value'
},
{
name: 'columns',
type: 'list',
label: 'Columns'
}
]
},
'pdFunc_merge': {
id: 'merge',
name: 'Merge',
library: 'pandas',
description: 'Merge 2 objects',
code: '${o0} = pd.merge(${i0}, ${i1}${v})',
input: [
{
name:'i0',
type:'var',
label: 'Left Dataframe',
component: 'var_select',
var_type: ['DataFrame']
},
{
name:'i1',
type:'var',
label: 'Right Dataframe',
component: 'var_select',
var_type: ['DataFrame']
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name:'left_on',
type:'text',
label: 'Left Key'
},
{
name:'right_on',
type:'text',
label: 'Right Key'
},
{
name:'how',
type:'text',
label: 'Merge Type',
component: 'option_select',
options: ['left', 'right', 'inner', 'outer']
},
{
name:'sort',
type:'bool',
label: 'Sort'
}
]
},
'pd009': {
id: 'join',
name: 'Join',
library: 'pandas',
description: 'Merge multiple objects',
code: '${o0} = ${i0}.join(${i1}${v})',
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame']
},
{
name:'i1',
type:'var',
label: 'Dataframe To Join',
component: 'var_select',
var_type: ['DataFrame']
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name:'on',
type:'text',
label: 'Key'
},
{
name:'how',
type:'text',
label: 'Type',
component: 'option_select',
options: ['left', 'right', 'inner', 'outer']
},
{
name:'sort',
type:'bool',
label: 'Sort',
component: 'bool_checkbox'
},
{
name:'lsuffix',
type:'text',
label: 'Left Suffix'
},
{
name:'rsuffix',
type:'text',
label: 'Right Suffix'
}
]
},
'pdFunc_concat': {
id: 'concat',
name: 'Concat',
library: 'pandas',
description: 'Merge multiple objects',
code: '${o0} = pd.concat([${i0}]${v})',
guide: [
's1 = pd.Series([0, 1], index=["a", "b"])',
's2 = pd.Series([2, 3, 4], index=["c", "d", "e"])',
'_concat = pd.concat([s1, s2], keys=["one", "two"], axis=1, sort=False, join="outer")',
'_concat'
],
input: [
{
name:'i0',
type:'list',
label: 'Target Variable',
component: 'var_multi',
var_type: ['DataFrame', 'Series']
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name:'index',
type:'list',
label:'Index List'
},
{
name:'axis',
type:'int',
label:'Axis',
help:'0:row / 1:column',
options:[0, 1],
options_label:['row', 'column'],
component:'option_select'
},
{
name:'sort',
type:'bool',
label:'Sort',
component: 'bool_checkbox'
},
{
name:'join',
type:'text',
label:'Join',
options: ['inner', 'outer'],
component: 'option_select'
}
]
},
'pdSdt_sortByIndex': {
id: 'sort_index',
name: 'Sort By Index',
library: 'pandas',
description: 'Sort by index',
code: '${o0} = ${i0}.sort_index(${v})',
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame', 'Series']
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name:'axis',
type:'int',
label: 'Sort By',
help: '0:row / 1:column',
component: 'option_select',
default: 0,
options: [0, 1],
options_label: ['row', 'column']
},
{
name:'ascending',
type:'bool',
label: 'Ascending Sort',
default: 'True',
component: 'bool_checkbox'
},
{
name:'inplace',
type:'bool',
label: 'Inplace',
default: 'False',
component: 'bool_checkbox'
},
{
name: 'kind',
type: 'text',
label: 'Sort Kind',
default: 'quicksort',
component: 'option_select',
options: ['quicksort', 'mergesort', 'heapsort'],
options_label: ['quicksort', 'mergesort', 'heapsort']
}
]
},
'pdGrp_groupby': {
id: 'groupby',
name: 'Group By',
library: 'pandas',
description: 'Group DataFrame/Series',
code: '${o0} = ${i0}.groupby(${level}${v})',
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame', 'Series']
},
{
name:'level',
type:['var', 'int', 'text'],
label: 'Grouping Column'
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name:'axis',
type:'int',
label: 'Axis',
help: '0:row / 1:column',
component: 'option_select',
options: [0, 1],
options_label: ['row', 'column']
},
{
name:'sort',
type:'bool',
label:'Sort',
component: 'bool_checkbox'
},
{
name: 'as_index',
type: 'bool',
label: 'Remove Index',
help: 'same as reset_index()',
component: 'bool_checkbox',
default: 'True'
}
]
},
'pdParr_period': {
id: 'period',
name: 'Period',
library: 'pandas',
description: 'Create Period object',
code: '${o0} = pd.Period(${i0}${v})',
input: [
{
name:'i0',
type:['int', 'text'],
label: 'Date'
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name: 'freq',
label: 'Frequency',
type: 'var',
component: 'option_select',
options: ['s', 'T', 'H', 'D', 'B', 'W', 'W-MON', 'M'],
options_label: ['second', 'minute', 'hour', 'day', 'weekdays', 'week(Sunday)', 'week(Monday)', 'last day of month']
},
{
index : 1,
name: 'year',
type: 'int',
label: 'Year'
},
{
index : 2,
name: 'month',
type: 'int',
label: 'Month'
},
{
index : 3,
name: 'day',
type: 'int',
label: 'Day'
}
]
},
'pdFunc_dropNA': {
id: 'dropna',
name: 'Drop NA',
library: 'pandas',
description: '',
code: '${o0} = ${i0}.dropna(${v})',
guide: [
'from numpy import nan as NA',
'data = Series([1, NA, 3.5, NA, 7])',
'cleaned = data.dropna()'
],
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame', 'Series']
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name: 'axis',
type:'int',
label: 'Axis',
help: '0:row / 1:column',
component: 'option_select',
options: [0, 1],
options_label: ['row', 'column']
},
{
name: 'how',
type: 'text',
label: 'How',
help: 'any: drop if na exist more than one\nall: drop if na exist every row/column',
component: 'option_select',
options: ['any', 'all']
},
{
name: 'thresh',
type: 'int',
label: 'Na Minimum Standard',
}
]
},
'pdFunc_fillNA': {
id: 'fillna',
name: 'Fill NA',
library: 'pandas',
description: 'replace null using value',
code: '${o0} = ${i0}.fillna(${v})',
guide: [
'from numpy import nan as NA',
'',
'df = pd.DataFrame([[1,2,3,NA],[4,NA,1,2],[0,9,6,7]])',
'df.fillna({1: 0.5, 3: -1})',
'df.fillna(0, inplace=True)'
],
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame', 'Series']
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name:'value',
type: ['var', 'int', 'dict'],
label: 'Value To Fill'
},
{
name: 'axis',
type:'int',
label: 'Axis',
help: '0:row / 1:column',
component: 'option_select',
default: 0,
options: [0, 1],
options_label: ['row', 'column']
},
{
name: 'method',
type: 'var',
label: 'How',
help: 'ffill:fill with before value\nbfill:fill with after value',
component: 'option_select',
default: 'None',
options: ['None', "'ffill'", "'bfill'"]
},
{
name: 'inplace',
type: 'bool',
label: 'Inplace',
component: 'bool_checkbox'
},
{
name: 'limit',
type: 'int',
label: 'Gap Limit'
}
]
},
'pdFunc_isDuplicated': {
id: 'duplicated',
name: 'Get Duplicates',
library: 'pandas',
description: 'Get duplicates',
code: '${o0} = ${i0}.duplicated(${v})',
guide: [
'data.duplicated()'
],
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame', 'Series']
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name: 'keep',
type:'var',
label: 'Mark Duplicated When',
component: 'option_select',
default: "'first'",
options: ["'first'", "'last'", 'False']
}
]
},
'pdFunc_dropDuplicates': {
id: 'drop_duplicates',
name: 'Drop Duplicates',
library: 'pandas',
description: 'Drop duplicates',
code: '${o0} = ${i0}.drop_duplicates(${v})',
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame', 'Series']
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name: 'keep',
type:'var',
label: 'Mark Duplicated When',
component: 'option_select',
default: "'first'",
options: ["'first'", "'last'", 'False']
}
]
},
'pdFunc_replace': {
id: 'replace_scala',
name: 'Scala Replace',
library: 'pandas',
description: 'Replace scala value',
code: '${o0} = ${i0}.replace(${v})',
guide: [
`s = pd.Series([0, 1, 2, 3, 4])`,
`s.replace(0, 5)`,
`df = pd.DataFrame({'A': [0, 1, 2, 3, 4],`,
` 'B': [5, 6, 7, 8, 9],`,
` 'C': ['a', 'b', 'c', 'd', 'e']})`,
`df.replace(0, 5)`
],
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame', 'Series']
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name:'to_replace',
type:'int',
label: 'To Replace',
required: true
},
{
name:'value',
type:'int',
label: 'Replace Value',
},
{
name: 'method',
type:'var',
label: 'Method',
options: ["'ffill'", "'bfill'", 'None'],
component: 'option_select',
default: "'ffill'"
}
]
},
'pd019': {
id: 'replace_list',
name: 'List-like Replace',
library: 'pandas',
description: 'Replace values using list',
code: '${o0} = ${i0}.replace(${v})',
guide: [
`df.replace([0, 1, 2, 3], 4)`,
`df.replace([0, 1, 2, 3], [4, 3, 2, 1])`,
`s.replace([1, 2], method='bfill')`
],
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame', 'Series']
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name:'to_replace',
type:'list',
label: 'To Replace',
required: true
},
{
name:'value',
type:['int', 'list'],
label: 'Value',
},
{
name: 'method',
type:'var',
label: 'Method',
options: ["'ffill'", "'bfill'", 'None'],
component: 'option_select',
default: "'ffill'"
}
]
},
'pd020': {
id: 'replace_dict',
name: 'Dict-like Replace',
library: 'pandas',
description: 'Replace values using dictionary',
code: '${o0} = ${i0}.replace(${v})',
guide: [
`df.replace({0: 10, 1: 100})`,
`df.replace({'A': 0, 'B': 5}, 100)`,
`df.replace({'A': {0: 100, 4: 400}})`
],
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame', 'Series']
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name:'to_replace',
type:'dict',
label: 'To Replace',
required: true
},
{
name:'value',
type:['int', 'dict'],
label: 'Value',
},
{
name: 'method',
type:'var',
label: 'Method',
options: ["'ffill'", "'bfill'", 'None'],
component: 'option_select',
default: "'ffill'"
}
]
},
// TODO: PENDING
'pd021': {
id: 'replace_regex',
name: 'Regular Expression Replace',
library: 'pandas',
description: '',
code: '${o0} = ${i0}.replace(${v})',
guide: [
`df = pd.DataFrame({'A': ['bat', 'foo', 'bait'],`,
` 'B': ['abc', 'bar', 'xyz']})`,
`df.replace(to_replace=r'^ba.$', value='new', regex=True)`,
`df.replace({'A': r'^ba.$'}, {'A': 'new'}, regex=True)`,
`df.replace(regex=r'^ba.$', value='new')`,
`df.replace(regex={r'^ba.$': 'new', 'foo': 'xyz'})`,
`df.replace(regex=[r'^ba.$', 'foo'], value='new')`
],
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame', 'Series']
}
],
output: [
{
name:'o0',
type:'var',
label:'Allocate to'
}
],
variable: [
{
name:'to_replace',
type:'dict',
label: 'To Replace',
required: true
},
{
name:'value',
type:['text', 'dict'],
label: 'Value',
},
{
name: 'method',
type:'var',
label: 'Method',
options: ["'ffill'", "'bfill'", 'None'],
component: 'option_select',
default: "'ffill'"
},
{
name: 'regex',
type:'bool',
label:'Regex',
options: [true, false]
}
]
},
'pdGrp_sum': {
id: 'sum',
name: 'Sum',
library: 'pandas',
description: '',
code: '${o0} = ${i0}.sum(${v})',
input: [
{
name:'i0',
type:'var',