Insert multiple columns in specific location based on two conditions in other columns

need to rewrite some code I already have. It insert columns where a 'Standard Deviation' column is missing. To do that it checks if the preceding column is a "variable" column, and if there already is a "Standard Deviation" column after it.

Right now I'm using a while loop that iterates through the columns checking df.iloc[1,x] and df.iloc[1,x+1].

i = 7
j = len(df.columns)-1

while i < j:
    if df.loc[1,i] != 'Standard Deviation' and df.loc[1,i] != 'Replicates' and df.loc[1,i] != 'Method':
        if df.loc[1,i+1] != 'Standard Deviation':
            df.insert(i+1,'Standard Deviation',np.nan)
            df.columns = pd.RangeIndex(df.columns.size)
            df.loc[1,i+1]='Standard Deviation'
    i+=1
    j = len(df.columns)-1

df.insert(len(df.columns),'Standard Deviation',np.nan)
df.columns = pd.RangeIndex(df.columns.size)
df.loc[1,len(df.columns)-1]='Standard Deviation'

Snippet from dataframe (hard to make sense of it):

50  51  52  53  54  55  56  57  58
0   Pour Point (°C) Pour Point (°C) Pour Point (°C) Pour Point (°C) Boiling Point Distribution- Temperature (°C)    Boiling Point Distribution- Temperature (°C)    Boiling Point Distribution- Temperature (°C)    Boiling Point Distribution- Temperature (°C)    Boiling Point Distribution- Temperature (°C)
1   Pour point  Standard Deviation  Replicates  Method  Initial Boiling Point   5%  10% 15% 20%
2   NaN NaN NaN NaN NaN NaN NaN NaN NaN
3   < -25   NaN NaN ASTM D97    NaN 35  52  70  88
4   < -25   NaN NaN ASTM D97    NaN 56  84  104 135
5   -6  NaN NaN ASTM D97    NaN 115 166 224 259
6   24  NaN NaN ASTM D97    NaN 279 303 322 339

Right now the code works and gives the expected outcome. I just want to rewrite it in a more efficient/elegant way.

I don't know how to do it without iterating over the columns to specify checking df.iloc[1,i] and df.iloc[1,i+1]