数值筛选
一、使用【】
1. 单条件筛选
最大逾期天数小于10
due_days=10
last_loan_df=last_loan_df[last_loan_df['max_due_days']<=due_days]
2. 多条件筛选
或
last_loan_df=last_loan_df[(last_loan_df['max_due_days']<=due_days )|(last_loan_df['score']>100) ]
且
last_loan_df=last_loan_df[(last_loan_df['max_due_days']<=due_days )&(last_loan_df['score']>100) ]
使用isin方法
# 选择某列等于多个数值或者字符串
last_loan_df[last_loan_df['custid'].isin([1,2,3,4,5])]
字符串的模糊筛选
一. .str.contains()
# 选含有wqbin|bin的行
df.loc[df['name'].str.contains('wqbin|bin']]
# 选不含wqbin或bin
df.loc[df['name'].str.contains('wqbin|bin'] == False]
注意：这里只能使用或（|）不能用且（&）
二. .str.startswith()
# 选姓wang的行
df.loc[df['name'].str.startswith('wang']]
完结！！
其实本质上还是调用了loc