read_json¶

In [ ]:

read_json(path: str,
          schema: str = "",
          table_name: str = "",
          usecols: list = [],
          new_name: dict = {},
          insert: bool = False,
          start_point: str = None,
          record_terminator: str = None,
          suppress_nonalphanumeric_key_chars: bool = False,
          reject_on_materialized_type_error: bool = False,
          reject_on_duplicate: bool = False,
          reject_on_empty_key: bool = False,
          flatten_maps: bool = True,
          flatten_arrays: bool = False,
          temporary_table: bool = False,
          temporary_local_table: bool = True,
          gen_tmp_table_name: bool = True,
          ingest_local: bool = True,
          genSQL: bool = False,
          materialize: bool = True,
          use_complex_dt: bool = False,)

Ingests a JSON file.

Parameters¶

Name	Type	Optional	Description
path	str	❌	Absolute path where the JSON file is located.
schema	str	✓	Schema where the JSON file will be ingested.
table_name	str	✓	Final relation name.
usecols	list	✓	List of the JSON parameters to ingest. The other ones will be ignored. If empty all the JSON parameters will be ingested.
new_name	dict	✓	Dictionary of the new columns name. If the JSON file is nested, it is advised to change the final names as special characters will be included. For example, {"param": {"age": 3, "name": Badr}, "date": 1993-03-11} will create 3 columns: "param.age", "param.name" and "date". You can rename these columns using the 'new_name' parameter with the following dictionary: {"param.age": "age", "param.name": "name"}
insert	bool	✓	If set to True, the data will be ingested to the input relation. The JSON parameters must be the same than the input relation otherwise they will not be ingested.
start_point	str	✓	String, name of a key in the JSON load data at which to begin parsing. The parser ignores all data before the start_point value. The value is loaded for each object in the file. The parser processes data after the first instance, and up to the second, ignoring any remaining data.
record_terminator	str	✓	When set, any invalid JSON records are skipped and parsing continues with the next record. Records must be terminated uniformly. For example, if your input file has JSON records terminated by newline characters, set this parameter to '\n'). If any invalid JSON records exist, parsing continues after the next record_terminator. Even if the data does not contain invalid records, specifying an explicit record terminator can improve load performance by allowing cooperative parse and apportioned load to operate more efficiently. When you omit this parameter, parsing ends at the first invalid JSON record.
suppress_nonalphanumeric_key_chars	bool	✓	Boolean, whether to suppress non-alphanumeric characters in JSON key values. The parser replaces these characters with an underscore (_) when this parameter is true.
reject_on_materialized_type_error	bool	✓	Boolean, whether to reject a data row that contains a materialized column value that cannot be coerced into a compatible data type. If the value is false and the type cannot be coerced, the parser sets the value in that column to null. If the column is a strongly-typed complex type, as opposed to a flexible complex type, then a type mismatch anywhere in the complex type causes the entire column to be treated as a mismatch. The parser does not partially load complex types.
reject_on_duplicate	bool	✓	Boolean, whether to ignore duplicate records (false), or to reject duplicates (true). In either case, the load continues.
reject_on_empty_key	bool	✓	Boolean, whether to reject any row containing a field key without a value.
flatten_maps	bool	✓	Boolean, whether to flatten all Avro maps. Key names are concatenated with nested levels. This value is recursive and affects all data in the load.
flatten_arrays	bool	✓	Boolean, whether to convert lists to sub-maps with integer keys. When lists are flattened, key names are concatenated as for maps. Lists are not flattened by default. This value affects all data in the load, including nested lists.
temporary_table	bool	✓	If set to True, a temporary table will be created.
temporary_local_table	bool	✓	If set to True, a temporary local table will be created and the parameter 'schema' is ignored.
gen_tmp_table_name	bool	✓	Sets the name of the temporary table. This parameter is only used when the parameter 'temporary_local_table' is set to True and if the parameters "table_name" and "schema" are unspecified.
ingest_local	bool	✓	If set to True, the file will be ingested from the local machine.
ingest_local	bool	✓	If set to True, the file will be ingested from the local machine.
genSQL	bool	✓	If set to True, the SQL code for creating the final table is generated but not executed. This is a good way to change the final relation types or to customize the data ingestion.
materialize	bool	✓	If set to True, the flex table is materialized into a table. Otherwise, it will remain a flex table. Flex tables simplify the data ingestion but have worse performace compared to regular tables.
use_complex_dt	bool	✓	Boolean, whether the input data file has complex structure. When this is true, most of the other parameters will be ignored.

Returns¶

vDataFrame : The vDataFrame of the relation.

Example¶

In [9]:

from verticapy.utilities import *
# Ingesting the JSON file
read_json("titanic.json", 
          table_name = "titanic_dataset",
          schema = "public")

The table "public"."titanic_dataset" has been successfully created.

	123 fields.parch Int	Abc Varchar(164)	Abc fields.sex Varchar(20)	010 fields.survived Boolean	Abc fields.ticket Varchar(36)	Abc fields.embarked Varchar(20)	123 fields.sibsp Int	📅 record_timestamp Timestamp	123 fields.passengerid Int	Abc Varchar(100)	123 fields.age Float	123 fields.fare Float	Abc fields.cabin Varchar(30)	123 fields.pclass Int	Abc datasetid Varchar(36)
1	0		male	❌	13049	C	0	2016-09-20 15:34:51.313	584		36.0	40.125	A10	1	titanic-passengers
2	0		male	❌	110465	S	0	2016-09-20 15:34:51.313	476		[null]	52.0	A14	1	titanic-passengers
3	0		female	✅	11755	C	1	2016-09-20 15:34:51.313	557		48.0	39.6	A16	1	titanic-passengers
4	0		male	❌	113056	S	0	2016-09-20 15:34:51.313	285		[null]	26.0	A19	1	titanic-passengers
5	0		male	✅	PC 17485	C	1	2016-09-20 15:34:51.313	600		49.0	56.9292	A20	1	titanic-passengers
6	0		male	✅	27042	S	0	2016-09-20 15:34:51.313	631		80.0	30.0	A23	1	titanic-passengers
7	0		male	❌	PC 17590	S	0	2016-09-20 15:34:51.313	868		31.0	50.4958	A24	1	titanic-passengers
8	0		male	✅	13213	C	0	2016-09-20 15:34:51.313	648		56.0	35.5	A26	1	titanic-passengers
9	0		male	✅	112277	C	0	2016-09-20 15:34:51.313	210		40.0	31.0	A31	1	titanic-passengers
10	0		male	❌	113767	S	0	2016-09-20 15:34:51.313	186		[null]	50.0	A32	1	titanic-passengers
11	2		male	✅	33638	S	0	2016-09-20 15:34:51.313	446		4.0	81.8583	A34	1	titanic-passengers
12	0		male	❌	112050	S	0	2016-09-20 15:34:51.313	807		39.0	0.0	A36	1	titanic-passengers
13	0		male	❌	PC 17754	C	0	2016-09-20 15:34:51.313	97		71.0	34.6542	A5	1	titanic-passengers
14	0		male	✅	113788	S	0	2016-09-20 15:34:51.313	24		28.0	35.5	A6	1	titanic-passengers
15	0		male	❌	17764	C	0	2016-09-20 15:34:51.313	175		56.0	30.6958	A7	1	titanic-passengers
16	0		male	✅	PC 17755	C	0	2016-09-20 15:34:51.313	738		35.0	512.3292	B101	1	titanic-passengers
17	0		male	❌	112058	S	0	2016-09-20 15:34:51.313	816		[null]	0.0	B102	1	titanic-passengers
18	1		female	✅	111361	C	0	2016-09-20 15:34:51.313	330		16.0	57.9792	B18	1	titanic-passengers
19	1		female	✅	111361	C	0	2016-09-20 15:34:51.313	524		44.0	57.9792	B18	1	titanic-passengers
20	0		male	❌	111240	S	0	2016-09-20 15:34:51.313	171		61.0	33.5	B19	1	titanic-passengers
21	0		female	✅	17474	S	1	2016-09-20 15:34:51.313	782		17.0	57.0	B20	1	titanic-passengers
22	0		male	✅	17474	S	1	2016-09-20 15:34:51.313	691		31.0	57.0	B20	1	titanic-passengers
23	2		female	✅	WE/P 5735	S	0	2016-09-20 15:34:51.313	541		36.0	71.0	B22	1	titanic-passengers
24	1		male	❌	WE/P 5735	S	1	2016-09-20 15:34:51.313	746		70.0	71.0	B22	1	titanic-passengers
25	0		female	✅	113572	[null]	0	2016-09-20 15:34:51.313	62		38.0	80.0	B28	1	titanic-passengers
26	0		female	✅	113572	[null]	0	2016-09-20 15:34:51.313	830		62.0	80.0	B28	1	titanic-passengers
27	1		female	✅	24160	S	0	2016-09-20 15:34:51.313	780		43.0	211.3375	B3	1	titanic-passengers
28	1		male	❌	113509	C	0	2016-09-20 15:34:51.313	55		65.0	61.9792	B30	1	titanic-passengers
29	0		female	✅	PC 17477	C	0	2016-09-20 15:34:51.313	370		24.0	69.3	B35	1	titanic-passengers
30	0		female	✅	PC 17477	C	0	2016-09-20 15:34:51.313	642		24.0	69.3	B35	1	titanic-passengers
31	0		male	❌	11771	C	0	2016-09-20 15:34:51.313	488		58.0	29.7	B37	1	titanic-passengers
32	0		male	❌	113050	S	0	2016-09-20 15:34:51.313	537		45.0	26.55	B38	1	titanic-passengers
33	2		female	✅	13568	C	0	2016-09-20 15:34:51.313	540		22.0	49.5	B39	1	titanic-passengers
34	0		female	✅	PC 17610	C	0	2016-09-20 15:34:51.313	195		44.0	27.7208	B4	1	titanic-passengers
35	1		male	✅	13567	C	1	2016-09-20 15:34:51.313	588		60.0	79.2	B41	1	titanic-passengers
36	0		female	✅	112053	S	0	2016-09-20 15:34:51.313	888		19.0	30.0	B42	1	titanic-passengers
37	0		female	✅	11967	C	1	2016-09-20 15:34:51.313	292		19.0	91.0792	B49	1	titanic-passengers
38	0		male	✅	11967	C	1	2016-09-20 15:34:51.313	485		25.0	91.0792	B49	1	titanic-passengers
39	1		female	✅	24160	S	0	2016-09-20 15:34:51.313	690		15.0	211.3375	B5	1	titanic-passengers
40	0		female	✅	24160	S	0	2016-09-20 15:34:51.313	731		29.0	211.3375	B5	1	titanic-passengers
41	0		male	✅	13214	C	0	2016-09-20 15:34:51.313	633		32.0	30.5	B50	1	titanic-passengers
42	0		male	❌	695	S	0	2016-09-20 15:34:51.313	873		33.0	5.0	B51 B53 B55	1	titanic-passengers
43	1		male	✅	PC 17755	C	0	2016-09-20 15:34:51.313	680		36.0	512.3292	B51 B53 B55	1	titanic-passengers
44	2		female	✅	PC 17608	C	2	2016-09-20 15:34:51.313	312		18.0	262.375	B57 B59 B63 B66	1	titanic-passengers
45	2		female	✅	PC 17608	C	2	2016-09-20 15:34:51.313	743		21.0	262.375	B57 B59 B63 B66	1	titanic-passengers
46	1		male	❌	PC 17558	C	0	2016-09-20 15:34:51.313	119		24.0	247.5208	B58 B60	1	titanic-passengers
47	1		female	✅	PC 17558	C	0	2016-09-20 15:34:51.313	300		50.0	247.5208	B58 B60	1	titanic-passengers
48	1		female	✅	12749	S	1	2016-09-20 15:34:51.313	821		52.0	93.5	B69	1	titanic-passengers
49	0		male	❌	F.C. 12750	S	1	2016-09-20 15:34:51.313	672		31.0	52.0	B71	1	titanic-passengers
50	0		female	✅	12749	S	0	2016-09-20 15:34:51.313	521		30.0	93.5	B73	1	titanic-passengers
51	0		female	✅	110152	S	0	2016-09-20 15:34:51.313	258		30.0	86.5	B77	1	titanic-passengers
52	0		female	✅	110152	S	0	2016-09-20 15:34:51.313	760		33.0	86.5	B77	1	titanic-passengers
53	0		female	✅	PC 17569	C	1	2016-09-20 15:34:51.313	32		[null]	146.5208	B78	1	titanic-passengers
54	0		female	✅	110152	S	0	2016-09-20 15:34:51.313	505		16.0	86.5	B79	1	titanic-passengers
55	0		female	✅	PC 17569	C	0	2016-09-20 15:34:51.313	196		58.0	146.5208	B80	1	titanic-passengers
56	0		male	❌	PC 17593	C	0	2016-09-20 15:34:51.313	790		46.0	79.2	B82 B84	1	titanic-passengers
57	0		male	❌	PC 17593	C	0	2016-09-20 15:34:51.313	140		24.0	79.2	B86	1	titanic-passengers
58	0		male	❌	112059	S	0	2016-09-20 15:34:51.313	264		40.0	0.0	B94	1	titanic-passengers
59	2		male	✅	113760	S	1	2016-09-20 15:34:51.313	803		11.0	120.0	B96 B98	1	titanic-passengers
60	2		female	✅	113760	S	1	2016-09-20 15:34:51.313	436		14.0	120.0	B96 B98	1	titanic-passengers
61	2		male	✅	113760	S	1	2016-09-20 15:34:51.313	391		36.0	120.0	B96 B98	1	titanic-passengers
62	2		female	✅	113760	S	1	2016-09-20 15:34:51.313	764		36.0	120.0	B96 B98	1	titanic-passengers
63	0		female	✅	11769	S	2	2016-09-20 15:34:51.313	572		53.0	51.4792	C101	1	titanic-passengers
64	0		female	✅	113783	S	0	2016-09-20 15:34:51.313	12		58.0	26.55	C103	1	titanic-passengers
65	0		male	✅	113786	S	0	2016-09-20 15:34:51.313	450		52.0	30.5	C104	1	titanic-passengers
66	0		male	✅	19988	S	0	2016-09-20 15:34:51.313	299		[null]	30.5	C106	1	titanic-passengers
67	0		male	❌	110465	S	0	2016-09-20 15:34:51.313	111		47.0	52.0	C110	1	titanic-passengers
68	0		male	❌	113051	C	0	2016-09-20 15:34:51.313	453		30.0	27.75	C111	1	titanic-passengers
69	1		male	❌	PC 17596	C	0	2016-09-20 15:34:51.313	274		37.0	29.7	C118	1	titanic-passengers
70	0		female	✅	113803	S	1	2016-09-20 15:34:51.313	4		35.0	53.1	C123	1	titanic-passengers
71	0		male	❌	113803	S	1	2016-09-20 15:34:51.313	138		37.0	53.1	C123	1	titanic-passengers
72	0		male	❌	113043	S	0	2016-09-20 15:34:51.313	332		45.5	28.5	C124	1	titanic-passengers
73	0		male	❌	113028	S	0	2016-09-20 15:34:51.313	712		[null]	26.55	C124	1	titanic-passengers
74	0		female	✅	PC 17582	S	0	2016-09-20 15:34:51.313	610		40.0	153.4625	C125	1	titanic-passengers
75	1		female	✅	PC 17582	S	0	2016-09-20 15:34:51.313	269		58.0	153.4625	C125	1	titanic-passengers
76	0		male	✅	19996	S	1	2016-09-20 15:34:51.313	713		48.0	52.0	C126	1	titanic-passengers
77	0		female	✅	19996	S	1	2016-09-20 15:34:51.313	670		[null]	52.0	C126	1	titanic-passengers
78	0		male	❌	113510	S	0	2016-09-20 15:34:51.313	352		[null]	35.0	C128	1	titanic-passengers
79	0		male	✅	111369	C	0	2016-09-20 15:34:51.313	890		26.0	30.0	C148	1	titanic-passengers
80	0		female	✅	113776	S	1	2016-09-20 15:34:51.313	152		22.0	66.6	C2	1	titanic-passengers
81	0		male	❌	113776	S	1	2016-09-20 15:34:51.313	337		29.0	66.6	C2	1	titanic-passengers
82	2		male	✅	113781	S	1	2016-09-20 15:34:51.313	306		0.92	151.55	C22 C26	1	titanic-passengers
83	2		female	❌	113781	S	1	2016-09-20 15:34:51.313	298		2.0	151.55	C22 C26	1	titanic-passengers
84	2		female	❌	113781	S	1	2016-09-20 15:34:51.313	499		25.0	151.55	C22 C26	1	titanic-passengers
85	2		male	❌	19950	S	3	2016-09-20 15:34:51.313	28		19.0	263.0	C23 C25 C27	1	titanic-passengers
86	2		female	✅	19950	S	3	2016-09-20 15:34:51.313	89		23.0	263.0	C23 C25 C27	1	titanic-passengers
87	2		female	✅	19950	S	3	2016-09-20 15:34:51.313	342		24.0	263.0	C23 C25 C27	1	titanic-passengers
88	4		male	❌	19950	S	1	2016-09-20 15:34:51.313	439		64.0	263.0	C23 C25 C27	1	titanic-passengers
89	0		male	❌	113787	S	0	2016-09-20 15:34:51.313	493		55.0	30.5	C30	1	titanic-passengers
90	0		female	✅	PC 17760	C	0	2016-09-20 15:34:51.313	326		36.0	135.6333	C32	1	titanic-passengers
91	0		female	✅	PC 17757	C	0	2016-09-20 15:34:51.313	717		38.0	227.525	C45	1	titanic-passengers
92	0		male	❌	19877	S	1	2016-09-20 15:34:51.313	742		36.0	78.85	C46	1	titanic-passengers
93	0		male	✅	11774	C	0	2016-09-20 15:34:51.313	840		[null]	29.7	C47	1	titanic-passengers
94	0		female	❌	PC 17595	C	0	2016-09-20 15:34:51.313	178		50.0	28.7125	C49	1	titanic-passengers
95	1		female	✅	11767	C	0	2016-09-20 15:34:51.313	880		56.0	83.1583	C50	1	titanic-passengers
96	0		male	✅	110564	S	0	2016-09-20 15:34:51.313	431		28.0	26.55	C52	1	titanic-passengers
97	0		male	✅	19947	S	0	2016-09-20 15:34:51.313	56		[null]	35.5	C52	1	titanic-passengers
98	0		female	✅	11767	C	0	2016-09-20 15:34:51.313	311		24.0	83.1583	C54	1	titanic-passengers
99	0		female	✅	PC 17757	C	1	2016-09-20 15:34:51.313	701		18.0	227.525	C62 C64	1	titanic-passengers
100	0		female	✅	PC 17758	C	1	2016-09-20 15:34:51.313	308		17.0	108.9	C65	1	titanic-passengers

Out[9]:

Rows: 1-100 of 891 | Columns: 15

In [11]:

# Ingesting the JSON file and renaming some columns
read_json("titanic.json", 
          table_name = "titanic_dataset",
          schema = "public",
          new_name = {"fields.fare": "fare",
                      "fields.sex": "sex"})

The table "public"."titanic_dataset" has been successfully created.

	123 fields.parch Int	Abc Varchar(164)	Abc sex Varchar(20)	010 fields.survived Boolean	Abc fields.ticket Varchar(36)	Abc fields.embarked Varchar(20)	123 fields.sibsp Int	📅 record_timestamp Timestamp	123 fields.passengerid Int	Abc Varchar(100)	123 fields.age Float	Abc fields.cabin Varchar(30)	123 fields.pclass Int	Abc datasetid Varchar(36)	123 fare Float
1	0		male	❌	13049	C	0	2016-09-20 15:34:51.313	584		36.0	A10	1	titanic-passengers	40.125
2	0		male	❌	110465	S	0	2016-09-20 15:34:51.313	476		[null]	A14	1	titanic-passengers	52.0
3	0		female	✅	11755	C	1	2016-09-20 15:34:51.313	557		48.0	A16	1	titanic-passengers	39.6
4	0		male	❌	113056	S	0	2016-09-20 15:34:51.313	285		[null]	A19	1	titanic-passengers	26.0
5	0		male	✅	PC 17485	C	1	2016-09-20 15:34:51.313	600		49.0	A20	1	titanic-passengers	56.9292
6	0		male	✅	27042	S	0	2016-09-20 15:34:51.313	631		80.0	A23	1	titanic-passengers	30.0
7	0		male	❌	PC 17590	S	0	2016-09-20 15:34:51.313	868		31.0	A24	1	titanic-passengers	50.4958
8	0		male	✅	13213	C	0	2016-09-20 15:34:51.313	648		56.0	A26	1	titanic-passengers	35.5
9	0		male	✅	112277	C	0	2016-09-20 15:34:51.313	210		40.0	A31	1	titanic-passengers	31.0
10	0		male	❌	113767	S	0	2016-09-20 15:34:51.313	186		[null]	A32	1	titanic-passengers	50.0
11	2		male	✅	33638	S	0	2016-09-20 15:34:51.313	446		4.0	A34	1	titanic-passengers	81.8583
12	0		male	❌	112050	S	0	2016-09-20 15:34:51.313	807		39.0	A36	1	titanic-passengers	0.0
13	0		male	❌	PC 17754	C	0	2016-09-20 15:34:51.313	97		71.0	A5	1	titanic-passengers	34.6542
14	0		male	✅	113788	S	0	2016-09-20 15:34:51.313	24		28.0	A6	1	titanic-passengers	35.5
15	0		male	❌	17764	C	0	2016-09-20 15:34:51.313	175		56.0	A7	1	titanic-passengers	30.6958
16	0		male	✅	PC 17755	C	0	2016-09-20 15:34:51.313	738		35.0	B101	1	titanic-passengers	512.3292
17	0		male	❌	112058	S	0	2016-09-20 15:34:51.313	816		[null]	B102	1	titanic-passengers	0.0
18	1		female	✅	111361	C	0	2016-09-20 15:34:51.313	330		16.0	B18	1	titanic-passengers	57.9792
19	1		female	✅	111361	C	0	2016-09-20 15:34:51.313	524		44.0	B18	1	titanic-passengers	57.9792
20	0		male	❌	111240	S	0	2016-09-20 15:34:51.313	171		61.0	B19	1	titanic-passengers	33.5
21	0		female	✅	17474	S	1	2016-09-20 15:34:51.313	782		17.0	B20	1	titanic-passengers	57.0
22	0		male	✅	17474	S	1	2016-09-20 15:34:51.313	691		31.0	B20	1	titanic-passengers	57.0
23	2		female	✅	WE/P 5735	S	0	2016-09-20 15:34:51.313	541		36.0	B22	1	titanic-passengers	71.0
24	1		male	❌	WE/P 5735	S	1	2016-09-20 15:34:51.313	746		70.0	B22	1	titanic-passengers	71.0
25	0		female	✅	113572	[null]	0	2016-09-20 15:34:51.313	62		38.0	B28	1	titanic-passengers	80.0
26	0		female	✅	113572	[null]	0	2016-09-20 15:34:51.313	830		62.0	B28	1	titanic-passengers	80.0
27	1		female	✅	24160	S	0	2016-09-20 15:34:51.313	780		43.0	B3	1	titanic-passengers	211.3375
28	1		male	❌	113509	C	0	2016-09-20 15:34:51.313	55		65.0	B30	1	titanic-passengers	61.9792
29	0		female	✅	PC 17477	C	0	2016-09-20 15:34:51.313	370		24.0	B35	1	titanic-passengers	69.3
30	0		female	✅	PC 17477	C	0	2016-09-20 15:34:51.313	642		24.0	B35	1	titanic-passengers	69.3
31	0		male	❌	11771	C	0	2016-09-20 15:34:51.313	488		58.0	B37	1	titanic-passengers	29.7
32	0		male	❌	113050	S	0	2016-09-20 15:34:51.313	537		45.0	B38	1	titanic-passengers	26.55
33	2		female	✅	13568	C	0	2016-09-20 15:34:51.313	540		22.0	B39	1	titanic-passengers	49.5
34	0		female	✅	PC 17610	C	0	2016-09-20 15:34:51.313	195		44.0	B4	1	titanic-passengers	27.7208
35	1		male	✅	13567	C	1	2016-09-20 15:34:51.313	588		60.0	B41	1	titanic-passengers	79.2
36	0		female	✅	112053	S	0	2016-09-20 15:34:51.313	888		19.0	B42	1	titanic-passengers	30.0
37	0		female	✅	11967	C	1	2016-09-20 15:34:51.313	292		19.0	B49	1	titanic-passengers	91.0792
38	0		male	✅	11967	C	1	2016-09-20 15:34:51.313	485		25.0	B49	1	titanic-passengers	91.0792
39	1		female	✅	24160	S	0	2016-09-20 15:34:51.313	690		15.0	B5	1	titanic-passengers	211.3375
40	0		female	✅	24160	S	0	2016-09-20 15:34:51.313	731		29.0	B5	1	titanic-passengers	211.3375
41	0		male	✅	13214	C	0	2016-09-20 15:34:51.313	633		32.0	B50	1	titanic-passengers	30.5
42	0		male	❌	695	S	0	2016-09-20 15:34:51.313	873		33.0	B51 B53 B55	1	titanic-passengers	5.0
43	1		male	✅	PC 17755	C	0	2016-09-20 15:34:51.313	680		36.0	B51 B53 B55	1	titanic-passengers	512.3292
44	2		female	✅	PC 17608	C	2	2016-09-20 15:34:51.313	312		18.0	B57 B59 B63 B66	1	titanic-passengers	262.375
45	2		female	✅	PC 17608	C	2	2016-09-20 15:34:51.313	743		21.0	B57 B59 B63 B66	1	titanic-passengers	262.375
46	1		male	❌	PC 17558	C	0	2016-09-20 15:34:51.313	119		24.0	B58 B60	1	titanic-passengers	247.5208
47	1		female	✅	PC 17558	C	0	2016-09-20 15:34:51.313	300		50.0	B58 B60	1	titanic-passengers	247.5208
48	1		female	✅	12749	S	1	2016-09-20 15:34:51.313	821		52.0	B69	1	titanic-passengers	93.5
49	0		male	❌	F.C. 12750	S	1	2016-09-20 15:34:51.313	672		31.0	B71	1	titanic-passengers	52.0
50	0		female	✅	12749	S	0	2016-09-20 15:34:51.313	521		30.0	B73	1	titanic-passengers	93.5
51	0		female	✅	110152	S	0	2016-09-20 15:34:51.313	258		30.0	B77	1	titanic-passengers	86.5
52	0		female	✅	110152	S	0	2016-09-20 15:34:51.313	760		33.0	B77	1	titanic-passengers	86.5
53	0		female	✅	PC 17569	C	1	2016-09-20 15:34:51.313	32		[null]	B78	1	titanic-passengers	146.5208
54	0		female	✅	110152	S	0	2016-09-20 15:34:51.313	505		16.0	B79	1	titanic-passengers	86.5
55	0		female	✅	PC 17569	C	0	2016-09-20 15:34:51.313	196		58.0	B80	1	titanic-passengers	146.5208
56	0		male	❌	PC 17593	C	0	2016-09-20 15:34:51.313	790		46.0	B82 B84	1	titanic-passengers	79.2
57	0		male	❌	PC 17593	C	0	2016-09-20 15:34:51.313	140		24.0	B86	1	titanic-passengers	79.2
58	0		male	❌	112059	S	0	2016-09-20 15:34:51.313	264		40.0	B94	1	titanic-passengers	0.0
59	2		male	✅	113760	S	1	2016-09-20 15:34:51.313	803		11.0	B96 B98	1	titanic-passengers	120.0
60	2		female	✅	113760	S	1	2016-09-20 15:34:51.313	436		14.0	B96 B98	1	titanic-passengers	120.0
61	2		male	✅	113760	S	1	2016-09-20 15:34:51.313	391		36.0	B96 B98	1	titanic-passengers	120.0
62	2		female	✅	113760	S	1	2016-09-20 15:34:51.313	764		36.0	B96 B98	1	titanic-passengers	120.0
63	0		female	✅	11769	S	2	2016-09-20 15:34:51.313	572		53.0	C101	1	titanic-passengers	51.4792
64	0		female	✅	113783	S	0	2016-09-20 15:34:51.313	12		58.0	C103	1	titanic-passengers	26.55
65	0		male	✅	113786	S	0	2016-09-20 15:34:51.313	450		52.0	C104	1	titanic-passengers	30.5
66	0		male	✅	19988	S	0	2016-09-20 15:34:51.313	299		[null]	C106	1	titanic-passengers	30.5
67	0		male	❌	110465	S	0	2016-09-20 15:34:51.313	111		47.0	C110	1	titanic-passengers	52.0
68	0		male	❌	113051	C	0	2016-09-20 15:34:51.313	453		30.0	C111	1	titanic-passengers	27.75
69	1		male	❌	PC 17596	C	0	2016-09-20 15:34:51.313	274		37.0	C118	1	titanic-passengers	29.7
70	0		female	✅	113803	S	1	2016-09-20 15:34:51.313	4		35.0	C123	1	titanic-passengers	53.1
71	0		male	❌	113803	S	1	2016-09-20 15:34:51.313	138		37.0	C123	1	titanic-passengers	53.1
72	0		male	❌	113043	S	0	2016-09-20 15:34:51.313	332		45.5	C124	1	titanic-passengers	28.5
73	0		male	❌	113028	S	0	2016-09-20 15:34:51.313	712		[null]	C124	1	titanic-passengers	26.55
74	0		female	✅	PC 17582	S	0	2016-09-20 15:34:51.313	610		40.0	C125	1	titanic-passengers	153.4625
75	1		female	✅	PC 17582	S	0	2016-09-20 15:34:51.313	269		58.0	C125	1	titanic-passengers	153.4625
76	0		male	✅	19996	S	1	2016-09-20 15:34:51.313	713		48.0	C126	1	titanic-passengers	52.0
77	0		female	✅	19996	S	1	2016-09-20 15:34:51.313	670		[null]	C126	1	titanic-passengers	52.0
78	0		male	❌	113510	S	0	2016-09-20 15:34:51.313	352		[null]	C128	1	titanic-passengers	35.0
79	0		male	✅	111369	C	0	2016-09-20 15:34:51.313	890		26.0	C148	1	titanic-passengers	30.0
80	0		female	✅	113776	S	1	2016-09-20 15:34:51.313	152		22.0	C2	1	titanic-passengers	66.6
81	0		male	❌	113776	S	1	2016-09-20 15:34:51.313	337		29.0	C2	1	titanic-passengers	66.6
82	2		male	✅	113781	S	1	2016-09-20 15:34:51.313	306		0.92	C22 C26	1	titanic-passengers	151.55
83	2		female	❌	113781	S	1	2016-09-20 15:34:51.313	298		2.0	C22 C26	1	titanic-passengers	151.55
84	2		female	❌	113781	S	1	2016-09-20 15:34:51.313	499		25.0	C22 C26	1	titanic-passengers	151.55
85	2		male	❌	19950	S	3	2016-09-20 15:34:51.313	28		19.0	C23 C25 C27	1	titanic-passengers	263.0
86	2		female	✅	19950	S	3	2016-09-20 15:34:51.313	89		23.0	C23 C25 C27	1	titanic-passengers	263.0
87	2		female	✅	19950	S	3	2016-09-20 15:34:51.313	342		24.0	C23 C25 C27	1	titanic-passengers	263.0
88	4		male	❌	19950	S	1	2016-09-20 15:34:51.313	439		64.0	C23 C25 C27	1	titanic-passengers	263.0
89	0		male	❌	113787	S	0	2016-09-20 15:34:51.313	493		55.0	C30	1	titanic-passengers	30.5
90	0		female	✅	PC 17760	C	0	2016-09-20 15:34:51.313	326		36.0	C32	1	titanic-passengers	135.6333
91	0		female	✅	PC 17757	C	0	2016-09-20 15:34:51.313	717		38.0	C45	1	titanic-passengers	227.525
92	0		male	❌	19877	S	1	2016-09-20 15:34:51.313	742		36.0	C46	1	titanic-passengers	78.85
93	0		male	✅	11774	C	0	2016-09-20 15:34:51.313	840		[null]	C47	1	titanic-passengers	29.7
94	0		female	❌	PC 17595	C	0	2016-09-20 15:34:51.313	178		50.0	C49	1	titanic-passengers	28.7125
95	1		female	✅	11767	C	0	2016-09-20 15:34:51.313	880		56.0	C50	1	titanic-passengers	83.1583
96	0		male	✅	110564	S	0	2016-09-20 15:34:51.313	431		28.0	C52	1	titanic-passengers	26.55
97	0		male	✅	19947	S	0	2016-09-20 15:34:51.313	56		[null]	C52	1	titanic-passengers	35.5
98	0		female	✅	11767	C	0	2016-09-20 15:34:51.313	311		24.0	C54	1	titanic-passengers	83.1583
99	0		female	✅	PC 17757	C	1	2016-09-20 15:34:51.313	701		18.0	C62 C64	1	titanic-passengers	227.525
100	0		female	✅	PC 17758	C	1	2016-09-20 15:34:51.313	308		17.0	C65	1	titanic-passengers	108.9

Out[11]:

Rows: 1-100 of 891 | Columns: 15

In [14]:

# Ingesting the JSON file, using some columns and
# renaming some columns
read_json("titanic.json", 
          table_name = "titanic_dataset",
          schema = "public",
          usecols = ["fields.fare", "fields.sex"],
          new_name = {"fields.fare": "fare",
                      "fields.sex": "sex"})

The table "public"."titanic_dataset" has been successfully created.

	Abc sex Varchar(20)	123 fare Float
1	male	0.0
2	male	0.0
3	male	0.0
4	male	0.0
5	male	0.0
6	male	0.0
7	male	0.0
8	male	0.0
9	male	0.0
10	male	0.0
11	male	0.0
12	male	0.0
13	male	0.0
14	male	0.0
15	male	0.0
16	male	4.0125
17	male	5.0
18	male	6.2375
19	male	6.4375
20	male	6.45
21	male	6.4958
22	male	6.4958
23	female	6.75
24	male	6.75
25	male	6.8583
26	male	6.95
27	male	6.975
28	male	6.975
29	male	7.0458
30	male	7.05
31	male	7.05
32	male	7.05
33	male	7.05
34	male	7.05
35	male	7.05
36	male	7.05
37	male	7.0542
38	male	7.0542
39	male	7.125
40	male	7.125
41	male	7.125
42	male	7.125
43	male	7.1417
44	female	7.225
45	female	7.225
46	male	7.225
47	male	7.225
48	male	7.225
49	male	7.225
50	male	7.225
51	male	7.225
52	male	7.225
53	male	7.225
54	male	7.225
55	male	7.225
56	female	7.2292
57	female	7.2292
58	male	7.2292
59	male	7.2292
60	male	7.2292
61	male	7.2292
62	male	7.2292
63	male	7.2292
64	male	7.2292
65	male	7.2292
66	male	7.2292
67	male	7.2292
68	male	7.2292
69	male	7.2292
70	male	7.2292
71	female	7.25
72	male	7.25
73	male	7.25
74	male	7.25
75	male	7.25
76	male	7.25
77	male	7.25
78	male	7.25
79	male	7.25
80	male	7.25
81	male	7.25
82	male	7.25
83	male	7.25
84	male	7.3125
85	female	7.4958
86	male	7.4958
87	male	7.4958
88	male	7.5208
89	female	7.55
90	female	7.55
91	male	7.55
92	male	7.55
93	female	7.6292
94	female	7.65
95	male	7.65
96	male	7.65
97	male	7.65
98	male	7.725
99	male	7.7292
100	female	7.7333

Out[14]:

Rows: 1-100 of 891 | Columns: 2

read_json¶

Parameters¶

Returns¶

Example¶

See Also¶