from ..check import _is_str, _is_str_list
[docs]class TimeRangeAggregation(object):
def __init__(self, df):
self._df = df
@property
def df(self):
return self._df
[docs] def num_users(self):
"""
Get the number of users in the Dataframe
:return: The number of users in the Dataframe
:rtype: int
"""
return self.df['userid'].nunique()
[docs] def user_id(self):
"""
Get the unique user ids in the Dataframe
:return: One-dimensional array of user ids in the event_stream
:rtype: List[str]
"""
return list(self.df['userid'].unique())
[docs] def contents_id(self):
"""
Get the unique contents ids in the Dataframe
:return: One-dimensional array of contents ids in the Dataframe
:rtype: List[str]
"""
return list(self.df['contentsid'].unique())
[docs] def operation_name(self):
"""
Get the unique operations in the Dataframe
:return: One-dimensional array of operation names in the Dataframe
:rtype: List[str]
"""
for column in self.df.columns:
if 'elapsed' in column:
elapsed_time = column
return list(self.df.columns.drop([elapsed_time, 'start_of_range', 'end_of_range', 'userid', 'contentsid', 'pageno']).values)
[docs] def operation_count(self, operation_name=None, user_id=None, contents_id=None):
"""
Get the count of each operations in the Dataframe
:param user_id: The user to count operation. If it is None, the total count of all users is returned.
:type user_id: str or None
:param contents_id: The contents to count operation. If it is None, the total count in all contents is returned.
:type contents_id: str or None
:param operation_name: The name of operation to count
:type operation_name: str or None
:return: If "operation_name" is None, return dictionary of the number of each operation in the Dataframe.
(Key: operation name, Value: The count of the operation)
else if "operation_name" is indicated, return the count of the operation
:rtype: dict or int
"""
df = self.df
if user_id is not None:
if _is_str(user_id) or not hasattr(user_id, "__iter__"):
df = df[df['userid'] == user_id]
elif _is_str_list(user_id):
df = df[df['userid'].isin(user_id)]
if contents_id is not None:
if _is_str(contents_id) or not hasattr(contents_id, "__iter__"):
df = df[df['contentsid'] == contents_id]
elif _is_str_list(contents_id):
df = df[df['contentsid'].isin(contents_id)]
for column in df.columns:
if 'elapsed' in column:
elapsed_time = column
operation_count_dict = dict(df.drop([elapsed_time, 'start_of_range', 'end_of_range', 'userid', 'contentsid', 'pageno'], axis=1).sum())
if operation_name is None:
return operation_count_dict
else:
if not _is_str(operation_name) and hasattr(operation_name, "__iter__"):
op_dict = {}
for op_name in operation_name:
op_dict[op_name] = operation_count_dict.get(op_name, 0)
return op_dict
else:
return operation_count_dict.get(operation_name, 0)
[docs] def to_csv(self, save_file):
if save_file[-4:] != ".csv":
save_file += ".csv"
self.df.to_csv(save_file, index=False, encoding="utf-8-sig")