Table Functions

This section describes table functions, including their syntax, parameters, and usage examples.

Function List

Function	Description
tab_parse_csv	Creates a table from a CSV file.
tab_to_dict	Creates a dictionary from a table.

tab_parse_csv

This function creates a table from a CSV file.

Function format

tab_parse_csv(data, sep=',', quote='"', lstrip=True, headers=None, case_insensitive=True, primary_keys=None)

Parameter description

Parameter	Type	Mandatory	Description
data	String	No	Text format. Generally, the CSV format is used.
sep	String	No	Delimiter. In CSV format, the default delimiter is commas (,).
quote	String	No	Quote character. If the value contains a delimiter, use quote characters to wrap it. The default quote character is the double quotation mark (").
lstrip	Boolean	No	Whether to delete the space at the beginning of each keyword. The default value is True.
headers	String or string list	No	Parsed domain information. By default, the first line is extracted. If the first line is data, this parameter needs to be transferred.
case_insensitive	Boolean	No	Whether the case is insensitive. The default value is True.
primary_keys	String or string list	No	Primary key in the data. If this parameter is set and the mapping enrichment function is used, the fields in the field parameter of the mapping enrichment function must align with the specified primary keys. For details about the mapping enrichment function, see Mapping and Enrichment Functions.

Returned result
The table mapped based on the CSV file.

Function example

Directly build a table and map a field value.

Test data
```
{
  "city": "nanjing"
}
```

Processing rule

e_table_map( 
  tab_parse_csv("province,city,pop,gdp\nshanghai,shanghai,2000,1000\njiangsu,nanjing,800,500"), 
  "city", 
  "province"
)

Processing result
```
city: nanjing
province: jiangsu
```

Directly build a table and map multiple field values.

Test data

{
  "city": "nanjing",
  "province": "jiangsu"
}

Processing rule

e_table_map( 
  tab_parse_csv("province,city,pop,gdp\nshanghai,shanghai,2000,1000\njiangsu,nanjing,800,500"), 
  ["province", "city"], 
  ["pop", "gdp"]
)

Processing result

city: nanjing
province: jiangsu
gdp: 500
pop: 800

If the mapping of multiple fields is different from the table column name, the first field in the source field brackets denotes the source field, and the second denotes the table field. In the target field brackets, the first field denotes the table field, and the second denotes the new field.
- Test data
```
{
  "city": "nanjing",
  "province": "jiangsu"
}
```
- Processing rule
```
e_table_map( 
  tab_parse_csv("prov,city,pop,gdp\nshanghai,shanghai,2000,1000\njiangsu,nanjing,800,500"), 
  [("province", "prov"), "city"], 
  [("pop", "population"), ("gdp", "GDP")]
)
```
- Processing result
```
city: nanjing
province: jiangsu
GDP: 500
population: 800
```

tab_to_dict

This function creates a dictionary from a table.

Function format

tab_to_dict(table, key_field, value_field, key_join=",", value_join=",")

Parameter description

Parameter	Type	Mandatory	Description
table	table	Yes	Table information.
key_field	String or string list	Yes	Table column used to construct dictionary keywords. Multiple columns need to be combined using key_join.
value_field	String or string list	Yes	Table column used to construct dictionary values. Multiple columns need to be combined using value_join.
key_join	String	No	Connection string for concatenating multiple columns of dictionary keywords. The default value is a comma (,).
value_join	String	No	Connection string for concatenating multiple columns of dictionary values. The default value is a comma (,).

Returned result
The dictionary mapped based on the table.

Function example

Directly build a table and map a field value.

Test data
```
{
  "k1": "v1",
  "city": "nj"
}
```

Processing rule

e_dict_map( 
  tab_to_dict(tab_parse_csv("city,pop\nsh,2000\nnj,800"), "city", "pop"), 
  "city", 
  "popu", 
)

Processing result
```
k1: v1
city: nj
popu: 800
```

Directly build a table and map multiple field values.

Test data
```
{
  "k1": "v1",
  "city": "js,nj"
}
```

Processing rule

e_dict_map( 
  tab_to_dict( 
    tab_parse_csv("province,city,pop\nsh,sh,2000\njs,nj,800"), 
    ["province", "city"], 
    "pop"
  ), 
  "city", 
  "popu"
)