CODEWITHSUNDEEP
pythonpandasdataframefloating-point
itsme 16may
itsme 16may

Reputation: 13

Compare float values in one column with all other columns in a pandas DataFrame

I have a dataframe with mutiple columns carrying float values.

df = pd.DataFrame({
        "v0": [0.493864,0.378362,0.342887,0.308959,0.746347], 
        "v1":[0.018915,0.018535,0.019587,0.035702,0.008325],
        "v2":[0.252000,0.066746,0.092421,0.036694,0.036506],
        "v3":[0.091409,0.103887,0.098669,0.112207,0.043911],
        "v4":[0.058429,0.312115,0.342887,0.305678,0.103065],
        "v5":[0.493864,0.378362,0.338524,0.304545,0.746347]})

I need to create another column result in df by comparing value of each row in df['v0'] with the value of rows in subsequent columns v1-v5.

What i need is as below: v0 v1 v2 v3 v4 v5 Result 0 0.493864 0.018915 0.252000 0.091409 0.058429 0.493864 1 1 0.378362 0.018535 0.066746 0.103887 0.312115 0.378362 1 2 0.342887 0.019587 0.092421 0.098669 0.342887 0.338524 1 3 0.308959 0.035702 0.036694 0.112207 0.305678 0.304545 0 4 0.746347 0.008325 0.036506 0.043911 0.103065 0.746347 1

I have tried many approaches including This link and This link

But it seems the task that I require is not doable. I have been struggling on this since last couple of days. The original dataset I have has more that 60000 rows. Please suggest the best and fastest way

Upvotes: 0

Views: 475

Answers (2)

itsme 16may
itsme 16may

Reputation: 13

For everyone the issue has been sorted. Thanks to all those wqho took time and replied to me. Being a amateur programmer, it was really heartening to see that my issue is getting answered. The final solution is arrived as below thanks to @coldspeed

JUPYTER NOTEBOOK SCREENSHOT

Upvotes: 0

cs95
cs95

Reputation: 402323

A better solution for dealing with floating point comparisons is to use np.isclose with broadcasting:

df['Result'] = np.isclose(v[:,1:], v[:,[0]]).any(1).astype(int)
df
         v0        v1        v2        v3        v4        v5  Result
0  0.493864  0.018915  0.252000  0.091409  0.058429  0.493864       1
1  0.378362  0.018535  0.066746  0.103887  0.312115  0.378362       1
2  0.342887  0.019587  0.092421  0.098669  0.342887  0.338524       1
3  0.308959  0.035702  0.036694  0.112207  0.305678  0.304545       0
4  0.746347  0.008325  0.036506  0.043911  0.103065  0.746347       1

Do NOT use equality based comparisons when dealing with floats because of the possibility of floating point inaccuracies. See Is floating point math broken?

Upvotes: 1

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