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]