CODEWITHSUNDEEP
pandasgrouping
leMiro
leMiro

Reputation: 13

Group repeating pattern in pandas Dataframe

so i have a Dataframe that has a repeating Number Series that i want to group like this:

Number Pattern Value Desired Group Value.1
1 723 1 Max of Group
2 400 1 Max of Group
8 235 1 Max of Group
5 387 2 Max of Group
7 911 2 Max of Group
3 365 3 Max of Group
4 270 3 Max of Group
5 194 3 Max of Group
7 452 3 Max of Group
100 716 4 Max of Group
104 69 4 Max of Group
2 846 5 Max of Group
3 474 5 Max of Group
4 524 5 Max of Group

So essentially the number pattern is always monotonly increasing.

Any Ideas?

Upvotes: 1

Views: 346

Answers (1)

jezrael
jezrael

Reputation: 862511

You can compare Number Pattern by 1 with cumulative sum by Series.cumsum and then is used GroupBy.transform with max:

df['Desired Group'] = df['Number Pattern'].eq(1).cumsum()
df['Value.1'] = df.groupby('Desired Group')['Value'].transform('max')
print (df)
    Number Pattern  Value  Desired Group  Value.1
0                1    723              1      723
1                2    400              1      723
2                3    235              1      723
3                1    387              2      911
4                2    911              2      911
5                1    365              3      452
6                2    270              3      452
7                3    194              3      452
8                4    452              3      452
9                1    716              4      716
10               2     69              4      716
11               1    846              5      846
12               2    474              5      846
13               3    524              5      846

For monotically increasing use:

df['Desired Group'] = (~df['Number Pattern'].diff().gt(0)).cumsum()

Upvotes: 1

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