使用 pandas 高效导入数据
Amany Mahfouz
Instructor
SELECT [column names] FROM [table name];SELECT date, tavg
FROM weather;
WHERE 子句选择性导入记录SELECT [column_names]
FROM [table_name]
WHERE [condition];
=> 和 >=< 和 <=<>(不等于)SELECT *
FROM weather
WHERE tmax > 32;
= 加目标文本精确匹配字符串/* 获取布鲁克林事件记录 */
SELECT *
FROM hpd311calls
WHERE borough = 'BROOKLYN';
# 载入库 import pandas as pd from sqlalchemy import create_engine# 创建数据库引擎 engine = create_engine("sqlite:///data.db")# 编写查询:获取布鲁克林的记录 query = """SELECT * FROM hpd311calls WHERE borough = 'BROOKLYN';"""# 查询数据库 brooklyn_calls = pd.read_sql(query, engine)print(brookyn_calls.borough.unique())
['BROOKLYN']
AND 的 WHERE 返回满足所有条件的记录# 编写查询:获取布朗克斯的管道相关记录 and_query = """SELECT * FROM hpd311calls WHERE borough = 'BRONX' AND complaint_type = 'PLUMBING';"""# 获取布朗克斯的管道问题来电 bx_plumbing_calls = pd.read_sql(and_query, engine) # 查看记录数 print(bx_plumbing_calls.shape)
(2016, 8)
OR 的 WHERE 返回满足任一条件的记录# 编写查询:获取渗水或管道相关记录 or_query = """SELECT * FROM hpd311calls WHERE complaint_type = 'WATER LEAK' OR complaint_type = 'PLUMBING';"""# 获取管道或渗水相关来电 leaks_or_plumbing = pd.read_sql(or_query, engine) # 查看记录数 print(leaks_or_plumbing.shape)
(10684, 8)
使用 pandas 高效导入数据