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How to add data to the categorical index of dataframe as data arrives? - AlekseyPython - Oct-07-2019
Python 3.7.3, pandas 0.25.1
I need to collect statistics within the clients, so I created a df in which for each client I group the necessary data:
#create dataframe
dtype=np.dtype([('day_begin','u4'), ('day_end','u4'), ('price_begin','f4'), ('price_end','f4'), ('Client','U13')])
auxiliary_array = np.empty(0, dtype=dtype)
periods_clients = pd.DataFrame(auxiliary_array)
periods_clients.set_index(['Client'], inplace=True)
#fill dataframe from file
with open(path_file) as csv_file:
reader = csv.reader(csv_file, delimiter=';')
fieldnames = ['Date', 'Client', 'Price']
reader = csv.DictReader(csv_file, fieldnames=fieldnames, delimiter=';')
for dict_str in reader:
Client = dict_str['Client']
if Client not in periods_clients.index:
periods_clients.loc[Client] = [current_date, current_date, current_price, current_price]
else:
periods_clients.loc[Client].day_end = current_date
periods_clients.loc[Client].price_end = current_priceThe client is a string field, so the program runs for a very long time. My attempt to replace this field with a categorical variable failed, because I could not add values while reading data from the file (and in advance I do not know all the clients). How to be, boys?
if I create catregorical index, then I get error:
#create dataframe
dtype=np.dtype([('day_begin','u4'), ('day_end','u4'), ('price_begin','f4'), ('price_end','f4')])
auxiliary_array = np.empty(0, dtype=dtype)
periods_clients = pd.DataFrame(auxiliary_array)
periods_clients['Client'] = pd.Series('Client', dtype='category')
periods_clients.set_index(['Client'], inplace=True)
....
#fill dataframe from file
...
if Client not in periods_clients.index:
periods_clients.index.add_categories(Client, inplace=True) #ERROR!!!Error:ValueError: cannot use inplace with CategoricalInRE: How to add data to the categorical index of dataframe as data arrives? - AlekseyPython - Oct-16-2019
Maybe there is some way?