CODEWITHSUNDEEP
pythonpandas
Junxu Chen
Junxu Chen

Reputation: 71

Find same value appeared in multiple columns

Suppose I have a dataframe

column1   column2   column3
  1          2        4
  2          3        5
  3          4        6
  4          5        7
  5          6        8

How would I able to find the values appear among these three columns?

Like in the above dataframe the output will be [4,5]

I tried the code

for index, row in df.iterrows():
   for i in row["column1"]:
       for j in row["column2"]:
           if row["column1"][i] == row["column2"][j]:
              print row["column1"][i]

and it jumps out the error

TypeError: 'numpy.float64' object is not iterable

I also tried

for i in df["column1"].iterrows():

and the error is

AttributeError: 'numpy.float64' object has no attribute 'iterrows'

Upvotes: 2

Views: 63

Answers (2)

BENY
BENY

Reputation: 323226

Try this:

s=df.melt().groupby('value').variable.nunique().loc[lambda x : x==df.shape[1]]
value
4    3
5    3
Name: variable, dtype: int64

#s.index.tolist()

Upvotes: 3

Vaishali
Vaishali

Reputation: 38415

You can use numpy intersect1d,

from functools import reduce
reduce(np.intersect1d, list(df.to_numpy().T))

Output: array([4, 5])

Upvotes: 2

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