具有以下内容:
engine = sqlalchemy.create_engine(url)
df = pd.DataFrame({
"eid": [1,2],
"f_i": [123, 1231],
"f_i_arr": [[123], [0]],
"f_53": ["2013/12/1","2013/12/1",],
"f_53a": [["2013/12/1"], ["2013/12/1"],],
})
with engine.connect() as con:
con.execute("""
DROP TABLE IF EXISTS public.test;
CREATE TABLE public.test
(
eid integer NOT NULL,
f_i INTEGER NULL,
f_i_arr INTEGER NULL,
f_53 DATE NULL,
f_53a DATE[] NULL,
PRIMARY KEY(eid)
);;
""")
df.to_sql("test", con, if_exists='append')
如果我尝试仅插入列“ f_53”(an date
),它将成功。
如果我尝试添加列“ f_53a”(a date[]
),它将失败并显示:
^
sqlalchemy.exc.ProgrammingError: (psycopg2.ProgrammingError) column "f_53a" is of type date[] but expression is of type text[]
LINE 1: ..._53, f_53a, f_i, f_i_arr) VALUES (1, '2013/12/1', ARRAY['201...
^
HINT: You will need to rewrite or cast the expression.
[SQL: 'INSERT INTO test (eid, f_53, f_53a, f_i, f_i_arr) VALUES (%(eid)s, %(f_53)s, %(f_53a)s, %(f_i)s, %(f_i_arr)s)'] [parameters: ({'f_53': '2013/12/1', 'f_53a': ['2013/12/1', '2013/12/1'], 'f_i_arr': [123], 'eid': 1, 'f_i': 123}, {'f_53': '2013/12/1', 'f_53a': ['2013/12/1', '2013/12/1'], 'f_i_arr': [0], 'eid': 2, 'f_i': 1231})]
是的-可以将数据框中的类型[]
和[][]
类型从数据框插入到Postgres中以形成数据框。
与平面DATE类型不同,这些类型可以由sql正确解析,DATE[]
并且DATE[][]
需要首先转换为datetime对象。像这样
with engine.connect() as con:
con.execute("""
DROP TABLE IF EXISTS public.test;
CREATE TABLE public.test
(
eid integer NOT NULL,
f_i INTEGER NULL,
f_ia INTEGER[] NULL,
f_iaa INTEGER[][] NULL,
f_d DATE NULL,
f_da DATE[] NULL,
f_daa DATE[][] NULL,
PRIMARY KEY(eid)
);
""")
d = pd.to_datetime("2013/12/1")
i = 99
df = pd.DataFrame({
"eid": [1,2],
"f_i": [i,i],
"f_ia": [None, [i,i]],
"f_iaa": [[[i,i],[i,i]], None],
"f_d": [d,d],
"f_da": [[d,d],None],
"f_daa": [[[d,d],[d,d]],None],
})
df.to_sql("test", con, if_exists='append', index=None)
本文收集自互联网,转载请注明来源。
如有侵权,请联系 [email protected] 删除。
我来说两句