指定主键update update tableA set owner = ? where id = ?...这种带有版本号或时间戳的,属于乐观锁方案,并发执行的sql,最先到的执行完之后,版本号发生变化,同一时刻并发的同版本号的update语句由于版本号对不上则无法udpate成功指定主键及与更新字段相关的条件...先到的sql先执行,而且owner发生变化,安排到后...
我们上篇文章中介绍了,如何加载excel和csv数据,其实除了这两种数据外,还可以从网站或者数据库中读取数据,这部分我们放到后面再和大家介绍。 有了数据,我们该如何查看呢,今天就和我一起看看如何查看数据的行,列的数据。 head()方法 我们先通过上次内容介绍的read_excel()方法将数据加载到pd这个变量 image-202312112225...
{SQL Server};SERVER='+server+';DATABASE='+database+';UID='+username+';PWD='+ password) cursor = cnxn.cursor()# select 26 rows from SQL table to insert in dataframe.query ="SELECT [CountryRegionCode], [Name] FROM Person.CountryRegion;"df = pd.read_sql(query, cnxn) print(df.head...
read_sql_query()中可以接受SQL语句,包括增删改查。但是DELETE语句不会返回值(但是会在数据库中执行),UPDATE,SELECT,等会返回结果. 例如:data = pd.read_sql_query('delete from test_cjk where f_intime = 1309',con = engine),这条语句会执行,删除 test_cjk表中f_intime=1309的值,但不会返回data。 其...
UPDATE数据更新 DELETE删除数据 0. 读取泰坦尼克数据集 import pandas as pd import numpy as np df = pd.read_csv("./datas/titanic/titanic_train.csv") df.head() 1. SELECT数据查询 # SQL: sql = """ SELECT PassengerId, Sex, Age, Survived FROM titanic LIMIT 5; """ # Pandas df[["Passen...
pivot_table([values, index, columns, …]) 创建电子表格样式的数据透视表作为DataFrame。plot pandas.plotting._core.PlotAccessor的别名pop(item) 返回项目并从框架中放下。pow(other[, axis, level, fill_value]) 获取数据帧和其他元素的指数幂(二进制运算符pow)。prod([axis, skipna, level, numeric_only...
=pd.read_csv(f"s3://YOUR_S3_BUCKET_AND_PATH/employees.csv",storage_options={"key":'YOUR_ACCESS_KEY',"secret":'YOUR_SECRET_KEY',},)jobs=MySQLConnector(config={"host":"YOUR_HOST","port":3306,"database":"hr","username":"YOUR_USER_NAME","password":"YOUR_PASSWORD",...
pivot_table() Create a spreadsheet pivot table as a DataFrame pop() Removes an element from the DataFrame pow() Raise the values of one DataFrame to the values of another DataFrame prod() Returns the product of all values in the specified axis product() Returns the product of the values ...
DataFrame.to_sql : Write to a SQL table. DataFrame.to_feather : Write out feather-format for DataFrames. DataFrame.to_csv : Write out to a csv file. Examples --- >>> df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]}, ... index=['a', 'b', 'c']) >>>...
# SQL: sql = """ SELECT PassengerId, Sex, Age, Survived FROM titanic LIMIT 5; """ In [ ] # Pandas df[["PassengerId", "Sex", "Age", "Survived"]].head(5) df.head(5)类似select * from table limit 5,查询所有的字段 2. WHERE按条件查询 In [ ] # SQL: sql = """ SELECT ...