Return Column name for specified value in pandas

You can compare all values of DataFrame and test at least one True by DataFrame.any - then mask is used for filter columns names:

c = df.columns[(df == 36.79).any()].tolist()

But because working with floats and possible some accuracy problems is better use numpy.isclose with select only numeric columns:

#if possible some non numeric columns
df1 = df.select_dtypes(np.number)
c = df1.columns[np.any(np.isclose(df1, 36.79), axis=0)].tolist()

#if all columns are numeric
c = df.columns[np.any(np.isclose(df, 36.79), axis=0)].tolist()

Sample:

print (df)
               Date   col1   col2   col3   col4   col5  col6   col7
0  01/01/2016 00:00  37.04  36.57  35.77  37.56  36.79  35.9  38.15
1  01/02/2016 00:00  37.04  36.57  35.77  37.56  36.79  35.9  36.79 <-last value changed

df1 = df.select_dtypes(np.number)
c = df1.columns[np.any(np.isclose(df1, 36.79), axis=0)].tolist()
print (c)
['col5', 'col7']

Last if want first matched value if exist is possible use next with iter for possible pass default value if empty list (no value match):

print (next(iter(c), 'no match'))
col5

df1 = df.select_dtypes(np.number)
c = df1.columns[np.any(np.isclose(df1, 100), axis=0)].tolist()
print (c)
[]

print (next(iter(c), 'no match'))
no match