You can use the pandas library to achieve what you want
[code]
import pandas as pd
count = {'lt60': {'a': 0, 'b': 0, 'c': 0, 'd': 0},
'ge60le90': {'a': 4, 'b': 0, 'c': 0, 'd': 0},
'gt90': {'a': 0, 'b': 1, 'c': 2, 'd': 1} }
df = pd.DataFrame(count).rename_axis('relation_type').reset_index()
df = df.rename(columns={'ge60le90': 'confidence<90',
'gt90': 'confidence>90',
'lt60': 'confidence<60'})
df.to_csv('out.csv', index=False)
# relation_type confidence<90 confidence>90 confidence<60
# 0 a 4 0 0
# 1 b 0 1 0
# 2 c 0 2 0
# 3 d 0 1 0
[/code]