CODEWITHSUNDEEP
pythonpandasdataframe
pc_pyr
pc_pyr

Reputation: 632

Python sum check in pandas dataframe

df1:

df1=pd.DataFrame({'id':['val1','val2','val3','val4','val5','val6'],
         'min':['10','10','75','42','20','50'],
         'max':['93','43','122','80','30','105']})

df2:

df2=pd.DataFrame({'id':['val1','val2','val5','val1','val5','val2'],
           'check':['55.4','35.8','93','11.5','23.8','3.22']})

The objective is to sum the corresponding check column values in df2 when id matches with df1 and check if the resultant sum is within min-max range in df1 and update values in result column of df2.

Output df: 

id            check        result
val1          55.4         positive
val2          35.8         positive
val5          93           positive
val3          10.1         negative
val1          11.5         positive
val5          23.8         positive
val2          3.22         positive

Many thanks!

Upvotes: 1

Views: 67

Answers (3)

ansev
ansev

Reputation: 30920

I think you need DataFrame.merge with GroupBy.transform. Then create a new column with np.where:

df3 = df2.merge(df1, how='left', on = 'id')
s = df3.groupby('id')['check'].transform('sum')
df2['result']=np.where(s.lt(df3['max']) & s.gt(df3['min']), 'positive', 'negative')
print(df2)

Output df2

     id check    result
0  val1  55.4  positive
1  val2  35.8  positive
2  val5    93  negative
3  val1  11.5  positive
4  val5  23.8  negative
5  val2  3.22  positive

Upvotes: 2

Quang Hoang
Quang Hoang

Reputation: 150745

We can merge and use between:

(df2.merge(df1, on='id', how='left')
   .assign(result=lambda x: np.where(x.check.between(x['min'],x['max']), 
                                     'positive', 'negative')
          )
   .drop(['min','max'], axis=1)
)

Output:

     id check    result
0  val1  55.4  positive
1  val2  35.8  positive
2  val5    93  negative
3  val1  11.5  positive
4  val5  23.8  positive
5  val2  3.22  positive

Upvotes: 2

BENY
BENY

Reputation: 323286

Let us do merge , the eval 

df=df2.merge(df1,how='left').eval('result=check>min and check < max')
Out[621]: 
     id check min max  result
0  val1  55.4  10  93    True
1  val2  35.8  10  43    True
2  val5    93  20  30   False
3  val1  11.5  10  93    True
4  val5  23.8  20  30    True
5  val2  3.22  10  43    True

Upvotes: 3

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