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define([
'nbextensions/visualpython/src/common/constant'
], function (vpConst) {
// TEST
// pandas 함수 설정값
/**
* Replaced with
'([a-zA-Z0-9_.]*)'[ ]*: (\{[\n\t ]*id:)[ ]*'([a-zA-Z0-9]*)'
'$3': $2 '$1'
*/
var _PANDAS_FUNCTION = {
'pd001': {
id: 'Series',
name: 'Series',
library: 'pandas',
description: '동일한 데이터 타입의 1차원 배열 생성',
code: '${o0} = pd.Series(${i0}${v})',
input: [
{
name:'i0',
type:['var', 'list', 'dict'],
label: 'Data'
}
],
output: [
{
name:'o0',
type:'var',
label:'Return to',
component: 'input_single'
}
],
variable: [
{
name:'index',
type:'list',
label: 'Index'
},
{
name:'name',
type:'text',
label:'Series Name'
}
]
},
'pd002': {
id: 'Dataframe',
name: 'DataFrame',
library: 'pandas',
description: '2차원의 Table 형태 변수 생성',
code: '${o0} = pd.DataFrame(${i0}${v})',
input: [
{
name:'i0',
type:['var', 'list2d', 'dict'],
label: 'Data',
component: 'table'
}
],
output: [
{
name:'o0',
type:'var',
label:'Return to'
}
],
variable: [
{
name:'index',
type:'list',
label:'Index List'
},
{
name:'columns',
type:'list',
label:'Column List'
}
]
},
'pd003': {
id: 'Index',
name: 'Index',
library: 'pandas',
description: '색인 객체 생성',
code: '${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'"],
options_label: ['객체', '선택 안 함', '정수형(32)', '정수형(64)', '실수형(32)', '실수형(64)', '문자형', '복소수(64bit)', 'bool형'],
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: 'Return to'
}
]
},
'pd004': {
id: 'read_csv',
name: 'Read CSV',
library: 'pandas',
description: '파일의 데이터를 읽어 DataFrame으로 생성',
code: '${o0} = pd.read_csv(${i0}${v})',
input: [
{
name:'i0',
type:'text',
label: 'File Path',
component: 'file'
}
],
output: [
{
name:'o0',
type:'var',
label:'Return to'
}
],
variable: [
{
name:'names',
type:'list',
label: 'Columns'
},
{
name:'usecols',
type: 'list',
label: 'Column List To Use'
},
{
name:'index_col',
type:'var',
label: 'Column To Use As Index'
},
{
name:'na_values',
type:'list',
label: 'Na Values'
},
{
name:'header',
type:'int',
label: 'Header Index'
},
{
name: 'sep',
type: 'text',
label: 'Seperator'
},
{
name: 'skiprows',
type: 'list',
label: 'Rows To Skip'
},
{
name: 'chunksize',
type: 'int',
label: 'Chunksize'
}
]
},
'pd005': {
id: 'to_csv',
name: 'To CSV',
library: 'pandas',
description: 'DataFrame을 csv 파일로 작성',
code: '${i0}.to_csv(${i1}${v})',
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame', 'Series']
},
{
name:'i1',
type:'text',
label: 'File Path',
component: 'file'
}
],
output: [
],
variable: [
{
name:'header',
type:['bool', 'list'],
label: 'Header Index',
default: 'True'
},
{
name: 'index',
type: 'bool',
label: 'Show 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'
}
]
},
'pd006': {
id: 'select_row',
name: '행 선택',
library: 'pandas',
description: '행 선택해 조회',
code: '${o0} = ${i0}[${i1}:${i2}]',
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame', 'Series']
},
{
name:'i1',
type:'int',
label: 'Start Row',
required: false
},
{
name:'i2',
type:'int',
label: 'End Row',
required: false
}
],
output: [
{
name:'o0',
type:'var',
label: 'Return to'
},
],
variable: [
]
},
'pd007': {
id: 'select_column',
name: '열 선택',
library: 'pandas',
description: '열 선택해 조회',
code: '${o0} = ${i0}[${i1}]',
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
var_type: ['DataFrame', 'Series'],
component: 'var_select'
},
{
name:'i1',
type:'list',
label: 'Columns',
required: false
}
],
output: [
{
name:'o0',
type:'var',
label: 'Return to'
},
],
variable: [
]
},
'pd008': {
id: 'merge',
name: 'Merge',
library: 'pandas',
description: '두 객체를 병합',
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:'Return 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: '다수의 객체를 병합',
code: '${o0} = ${i0}.join(${i1}${v})',
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame']
},
{
name:'i1',
type:'var',
label: 'Dataframe To Join',
component: 'var_select',
var_type: ['DataFrame']
}
],
output: [
{
name:'o0',
type:'var',
label:'Return to'
}
],
variable: [
{
name:'on',
type:'text',
label: 'Key'
},
{
name:'how',
type:'text',
label: 'Type',
component: 'option_select',
options: ['left', 'right', 'inner', 'outer']
},
{
name:'sort',
type:'bool',
label: 'Sort',
component: 'bool_checkbox'
},
{
name:'lsuffix',
type:'text',
label: 'Left Suffix'
},
{
name:'rsuffix',
type:'text',
label: 'Right Suffix'
}
]
},
'pd010': {
id: 'concat',
name: 'Concat',
library: 'pandas',
description: '다수의 객체를 병합',
code: '${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:'Return 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'
}
]
},
'pd011': {
id: 'sort_index',
name: 'Sort By Index',
library: 'pandas',
description: 'DataFrame/Series 객체를 index 기준으로 정렬',
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:'Return 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']
}
]
},
'pd012': {
id: 'groupby',
name: 'Group By',
library: 'pandas',
description: 'DataFrame/Series 객체의 그룹화',
code: '${o0} = ${i0}.groupby(${level}${v})',
input: [
{
name:'i0',
type:'var',
label: 'Target Variable',
component: 'var_select',
var_type: ['DataFrame', 'Series']
},
{
name:'level',
type:['var', 'int', 'text'],
label: 'Grouping Column'
}
],
output: [
{
name:'o0',
type:'var',
label:'Return to'
}
],
variable: [
{
name:'axis',
type:'int',
label: 'Axis',
help: '0:row / 1:column',
component: 'option_select',
options: [0, 1],
options_label: ['row', 'column']
},
{
name:'sort',
type:'bool',
label:'Sort',
component: 'bool_checkbox'
},
{
name: 'as_index',
type: 'bool',
label: 'Remove Index',
help: 'same as reset_index()',
component: 'bool_checkbox',
default: true
}
]
},
'pd013': {
id: 'period',
name: 'Period',
library: 'pandas',
description: 'Period 객체 생성',
code: '${o0} = pd.Period(${i0}${v})',
input: [
{
name:'i0',
type:['int', 'text'],
label: 'Date'
}
],
output: [
{
name:'o0',
type:'var',
label:'Return to'
}
],
variable: [
{
name: 'freq',
label: 'Frequency',
type: 'var',
component: 'option_select',
options: ['s', 'T', 'H', 'D', 'B', 'W', 'W-MON', 'M'],
options_label: ['초', '분', '시간', '일', '주말이 아닌 평일', '주(일요일)', '주(월요일)', '각 달의 마지막 날']
},
{
index : 1,
name: 'year',
type: 'int',
label: 'Year'
},
{
index : 2,
name: 'month',
type: 'int',
label: 'Month'
},
{
index : 3,
name: 'day',
type: 'int',
label: 'Day'
}
]
},
'pd014': {
id: 'dropna',
name: 'Drop NA',
library: 'pandas',
description: 'dropna()로 결측치 처리',
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:'Return 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',
help: '결측치가 몇 개일 때 부터 제거할지 개수 입력'
}
]
},
'pd015': {
id: 'fillna',
name: 'Fill NA',
library: 'pandas',
description: 'fillna()로 널 값 대체',
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]])',
'# dictionary 형식으로 받았는데 앞의 key가 컬럼을 나타낸다',
'df.fillna({1: 0.5, 3: -1})',
'# fillna는 값을 채워 넣은 객체의 참조를 반환한다',
'_ = 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:'Return 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'"],
options_label: ['선택 안 함', '이전 값으로 채우기', '이후 값으로 채우기']
},
{
name: 'inplace',
type: 'bool',
label: 'Inplace',
component: 'bool_checkbox'
},
{
name: 'limit',
type: 'int',
label: 'Gap Limit',
help: '전/후 보간 시에 사용할 최대 갭 크기'
}
]
},
'pd016': {
id: 'duplicated',
name: 'Get Duplicates',
library: 'pandas',
description: '중복 조회',
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:'Return to'
}
],
variable: [
{
name: 'keep',
type:'var',
label: 'Mark Duplicated When',
help: 'first:첫 번째 항목 뺀 모두 중복으로 표시 / last:마지막 항목 뺀 모두 중복으로 표시 / False:모두 중복으로 표시',
component: 'option_select',
default: "'first'",
options: ["'first'", "'last'", 'False'],
options_label: ['첫 번째 항목 제외한 모두 중복으로 표시', '마지막 항목 제외한 모두 중복으로 표시', '모두 중복으로 표시']
}
]
},
'pd017': {
id: 'drop_duplicates',
name: 'Drop Duplicates',
library: 'pandas',
description: '중복된 항목 제거',
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:'Return to'
}
],
variable: [
{
name: 'keep',
type:'var',
label: 'Mark Duplicated When',
help: 'first:첫 번째 항목 뺀 모두 중복으로 표시 / last:마지막 항목 뺀 모두 중복으로 표시 / False:모두 중복으로 표시',
component: 'option_select',
default: "'first'",
options: ["'first'", "'last'", 'False'],
options_label: ['첫 번째 항목 제외한 모두 중복으로 표시', '마지막 항목 제외한 모두 중복으로 표시', '모두 중복으로 표시']
}
]
},
'pd018': {
id: 'replace_scala',
name: 'Scala Replace',
library: 'pandas',
description: 'Scala 값 치환',
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:'Return 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'],
options_label: ['이전 값으로 채우기', '이후 값으로 채우기', '선택 안 함'],
component: 'option_select',
default: "'ffill'"
}
]
},
'pd019': {
id: 'replace_list',
name: 'List-like Replace',
library: 'pandas',
description: 'List 값 치환',
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:'Return 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'],
options_label: ['이전 값으로 채우기', '이후 값으로 채우기', '선택 안 함'],
component: 'option_select',
default: "'ffill'"
}
]
},
'pd020': {
id: 'replace_dict',
name: 'Dict-like Replace',
library: 'pandas',
description: 'Dictionary 값 치환',
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:'Return 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'],
options_label: ['이전 값으로 채우기', '이후 값으로 채우기', '선택 안 함'],
component: 'option_select',
default: "'ffill'"
}
]
},
// TODO: 정규식은 PENDING