Find Row Closest Value To Input

I am struggling with this problem. I have an pandas array which looks like this delta_n column_1 ... 0 10 10 ... 1 20

Solution 1:

Subtract value by sub, get absolute values by abs, find index with minimal value by idxmin and last select by loc:

idx = df['delta_n'].sub(delta_n).abs().idxmin()

#added double [[]] for one row DataFrame
df1 = df.loc[[idx]]
print (df1)
   delta_n  column_1
1       20         0

#output Series with one []
s = df.loc[idx]
print (s)
delta_n     20
column_1     0
Name: 1, dtype: int64

Details:

print (df['delta_n'].sub(delta_n))
0   -10.5
1    -0.5
2     9.5
Name: delta_n, dtype: float64

print (df['delta_n'].sub(delta_n).abs())
0    10.5
1     0.5
2     9.5
Name: delta_n, dtype: float64

print (df['delta_n'].sub(delta_n).abs().idxmin())
1

Another numpy solution for positions by numpy.argmin and selecting by iloc:

pos = df['delta_n'].sub(delta_n).abs().values.argmin()
print (pos)
1

df1 = df.loc[[pos]]
print (df1)
   delta_n  column_1
1       20         0

s = df.loc[pos]
print (s)
delta_n     20
column_1     0
Name: 1, dtype: int64