pandas
SQL Server에서 Dataframe으로 읽기
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pyodbc 사용
import pandas.io.sql
import pyodbc
import pandas as pd
매개 변수 지정
# Parameters
server = 'server_name'
db = 'database_name'
UID = 'user_id'
연결 만들기
# Create the connection
conn = pyodbc.connect('DRIVER={SQL Server};SERVER=' + server + ';DATABASE=' + db + '; UID = ' + UID + '; PWD = ' + UID + 'Trusted_Connection=yes')
팬더 데이터 프레임에 대한 질의
# Query into dataframe
df= pandas.io.sql.read_sql('sql_query_string', conn)
연결 루프와 함께 pyodbc 사용하기
import os, time
import pyodbc
import pandas.io.sql as pdsql
def todf(dsn='yourdsn', uid=None, pwd=None, query=None, params=None):
''' if `query` is not an actual query but rather a path to a text file
containing a query, read it in instead '''
if query.endswith('.sql') and os.path.exists(query):
with open(query,'r') as fin:
query = fin.read()
connstr = "DSN={};UID={};PWD={}".format(dsn,uid,pwd)
connected = False
while not connected:
try:
with pyodbc.connect(connstr,autocommit=True) as con:
cur = con.cursor()
if params is not None: df = pdsql.read_sql(query, con,
params=params)
else: df = pdsql.read_sql(query, con)
cur.close()
break
except pyodbc.OperationalError:
time.sleep(60) # one minute could be changed
return df
Modified text is an extract of the original Stack Overflow Documentation
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