答案 0 :(得分:0)
我也从来没有直接使用过MySQL连接器。现在已经安装了,尝试使用sqlalchemy和pandas的组合。熊猫可以为您创建表,这将大大减少您的代码。
import sqlalchemy
import pandas as pd
# MySQL database connection
engine_stmt = 'mysql+mysqldb://%s:%s@%s:3306/%s' % (username, password,
server,database)
engine = sqlalchemy.create_engine(engine_stmt)
# get your data into pandas
df = pd.read_csv("file/location/name.csv")
# adjust your dataframe as you want it to look in the database
df = df.rename(columns={0: 'yearquarter', 1: 'sms_volumes')
# using your existing function to assign start/end row by row
for index, row in df.iterrows():
dt_start, dt_end = getdatesfromquarteryear(row['yearquarter'])
df.loc[index, 'sms_start_date'] = dt_start
df.loc[index, 'sms_end_date'] = dt_end
# write the entire dataframe to database
df.to_sql(name='sms_volumes', con=engine,
if_exists='append', index=False, chunksize=1000)
print('All data inserted!')
与read_csv()类似,Pandas可以使将表中的数据轻松返回到数据框中:
# create a new dataframe from your existing table
new_df = pd.read_sql("SELECT * FROM sms_volumes", engine)