Python2.7：在DataFrame组中进行比较并根据条件进行过滤
[英]Python2.7: Compare within DataFrame groups and filter based on condition
问题描述
I have a pandas dataframe which i plan to group by 'name', 'driverRef', 'tyre' and filter only groups which have similar values in one column. 
我有一个熊猫数据框，我打算按“名称”，“ driverRef”，“轮胎”进行分组，并只过滤一列中具有相似值的组。
Within the group, all rows have the same value in that column. 在该组中，所有行在该列中具有相同的值。
Similar is defined as at most a range of 3 in difference between values.
相似被定义为值之间的差异最大为3的范围。
eg.
例如。
if the unique numbers in the column are 5, 10, 12, 13, only groups with 10,12,13 are kept.
如果列中的唯一数字是5、10、12、13，则仅保留具有10、12、13的组。
EDIT: The similarity criteria i planned originally is ambiguous, i have changed it to simply the mode of the group. 编辑：我最初计划的相似性标准是模棱两可的，我已将其更改为简单的小组模式。
name driverRef stint tyre lap stint length
0 Australian Grand Prix ham 1.0 Super soft 1 5
1 Australian Grand Prix vettel 1.0 Super soft 2 10
2 Australian Grand Prix bottas 1.0 Super soft 3 10
3 Australian Grand Prix alonso 2.0 Super soft 20 13
4 Australian Grand Prix alonso 2.0 Super soft 21 13
5 Australian Grand Prix alonso 2.0 Super soft 22 13
6 Bahrain Grand Prix ham 1.0 Super soft 1 5
7 Bahrain Grand Prix vettel 1.0 Super soft 2 6
8 Bahrain Grand Prix bottas 1.0 Super soft 3 6
9 Bahrain Grand Prix alonso 2.0 Super soft 20 13
10 Bahrain Grand Prix alonso 2.0 Super soft 21 13
11 Bahrain Grand Prix alonso 2.0 Super soft 22 13
Expected output: 预期产量：
name driverRef stint tyre lap stint length
4 Australian Grand Prix alonso 2.0 Super soft 21 13
5 Australian Grand Prix alonso 2.0 Super soft 22 13
9 Bahrain Grand Prix alonso 2.0 Super soft 20 13
10 Bahrain Grand Prix alonso 2.0 Super soft 21 13
11 Bahrain Grand Prix alonso 2.0 Super soft 22 13
1 个解决方案
解决方案1
0 2018-02-25 14:13:05
I believe you need: 我相信您需要：
s = df.groupby(['name','tyre'])['stint length'].transform(lambda x: x.mode().iat[0])
#alternative
#s=df.groupby(['name','tyre'])['stint length'].transform(lambda x:x.value_counts().index[0])
df = df[df['stint length'] == s]
print (df)
name driverRef stint tyre lap stint length
3 Australian Grand Prix alonso 2.0 Super soft 20 13
4 Australian Grand Prix alonso 2.0 Super soft 21 13
5 Australian Grand Prix alonso 2.0 Super soft 22 13
9 Bahrain Grand Prix alonso 2.0 Super soft 20 13
10 Bahrain Grand Prix alonso 2.0 Super soft 21 13
11 Bahrain Grand Prix alonso 2.0 Super soft 22 13
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