Bears is a fast and simple alternative to Pandas.
- Fast indexing
# with dict
DataFrame(data={'col1':arr1, 'col2':arr2})
# with keys/values
DataFrame(keys=['col1','col2'],values=[arr1,arr2])
The recommended way for performance is to get records without column names. You can index a specific column with df.<column_name>.
df[5] # [arr1[5], arr2[5]]
df[[1,3]] # DataFrame(data={'col1':arr1[[1,3]], 'col2':arr2[[1,3]]})
df[5:6] # DataFrame(data={'col1':arr1[5:6], 'col2':arr2[5:6]})
scalar = df[5][df.col1]
df.rows_value() # [arr1, arr2]
df.rows_value([1,2]) # [arr1[1,2], arr2[1,2]]
df.rows_dict() # [ {'col1': arr1[0], 'col2': arr2[0]}, {'col1': arr1[1], 'col2': arr2[1]} ]
df.rows_dict([1]) # [ {'col1': arr1[1], 'col2': arr2[1]} ]
df.to_dict() # {'col1': arr1, 'col2': arr2}
df.to_dict([1,3,5]) # {'col1': arr1[1,3,5], 'col2': arr2[1,3,5]}