Efficient way of looping through list of dictionaries and appending items into column in dataframe

One idea is pass data to DataFrame cosntructor and then use rename:

df = pd.DataFrame(data).rename(columns={'1':'col1'})
print (df)
   col1
0    20
1    10
2    40
3    14
4    33

If is necessary filtering use list comprehension and add parameter columns:

df = pd.DataFrame([x['1'] for x in data], columns=['col1'])
print (df)
   col1
0    20
1    10
2    40
3    14
4    33

EDIT: For new data use:

data = [
    {'1':
     {'value':20}},
    {'1':
     {'value':10}},
    {'1':
      {'value':40}},
    {'1':
      {'value':14}},
    {'1':
      {'value':33}}]

df = pd.DataFrame([x['1']['value'] for x in data], columns=['col1'])
print (df)
   col1
0    20
1    10
2    40
3    14
4    33

Or:

df = pd.DataFrame([x['1'] for x in data]).rename(columns={'value':'col1'})
print (df)
   col1
0    20
1    10
2    40
3    14
4    33

@jezrael's answer is correct but to be more specific with col:

df = pd.DataFrame(data)
print(df.add_prefix('col'))

Output:

   col1
0    20
1    10
2    40
3    14
4    33