[英]Retrieving rows from Pandas DataFrame based on month of a date column in a range
I currently have a table called Sales
.我目前有一个名为
Sales
的表。 The Sales
table has a column called sale_date
which is in the form YYYY-MM-DD
and I want to extract rows where the month is within a range. Sales
表有一个名为sale_date
的列,其格式YYYY-MM-DD
,我想提取月份在一个范围内的行。
| seller_id | product_id | buyer_id | sale_date | quantity | price |
|-----------|------------|----------|--------------|----------|-------|
| 7 | 11 | 49 | '2019-01-21' | 5 | 3330 |
| 13 | 32 | 6 | '2019-02-10' | 9 | 1089 |
| 50 | 47 | 4 | '2019-01-06' | 1 | 1343 |
I've tried something like:我试过类似的东西:
>>> df.loc[df['sale_date'].str.split('-').isin([1, 2, 3])]
>>> df.loc[[int(x[1]) for x in df['sale_date'].str.split('-')][1] in [1, 2, 3]]
but these result in a type error and key error, respectively.但是这些分别导致类型错误和键错误。
Is there any way that I can extract just the month from the sale_date
column and check whether it's in a range?有什么方法可以从
sale_date
列中提取月份并检查它是否在一个范围内? Thanks.谢谢。
You can convert values to datetimes and then extract months:您可以将值转换为日期时间,然后提取月份:
df.loc[pd.to_datetime(df['sale_date']).dt.month.isin([1, 2, 3])]
Or modify your solution with extract second values from list by indexing str[1]
with casting to integers:或者通过索引
str[1]
并转换为整数来修改您的解决方案,从列表中提取第二个值:
df.loc[df['sale_date'].str.split('-').str[1].astype(int).isin([1, 2, 3])]
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