Use numpy and pd.DataFrame
def pir(df):
nans = np.where(np.empty_like(df.values), np.nan, np.nan)
data = np.hstack([nans, df.values]).reshape(-1, df.shape[1])
return pd.DataFrame(data, columns=df.columns)
pir(df1)

Testing and Comparison
the code
def banana(df):
df1 = df.set_index(np.arange(1, 2*len(df)+1, 2))
df2 = pd.DataFrame(index=range(0, 2*len(df1), 2), columns=df1.columns)
return pd.concat([df1, df2]).sort_index()
def anton(df):
df = df.set_index(np.arange(1, 2*len(df)+1, 2))
return df.reindex(index=range(2*len(df)))
def pir(df):
nans = np.where(np.empty_like(df.values), np.nan, np.nan)
data = np.hstack([nans, df.values]).reshape(-1, df.shape[1])
return pd.DataFrame(data, columns=df.columns)
results
pd.concat([f(df1) for f in [banana, anton, pir]],
axis=1, keys=['banana', 'anton', 'pir'])

Timing

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