|
1
|
|
|
""" |
|
2
|
|
|
Data Manipulation class |
|
3
|
|
|
""" |
|
4
|
|
|
# package to add support for multi-language (i18n) |
|
5
|
|
|
import gettext |
|
6
|
|
|
# package to handle files/folders and related metadata/operations |
|
7
|
|
|
import os |
|
8
|
|
|
|
|
9
|
|
|
|
|
10
|
|
|
class DataManipulator: |
|
11
|
|
|
locale = None |
|
12
|
|
|
|
|
13
|
|
|
def __init__(self, in_language='en_US'): |
|
14
|
|
|
current_script = os.path.basename(__file__).replace('.py', '') |
|
15
|
|
|
lang_folder = os.path.join(os.path.dirname(__file__), current_script + '_Locale') |
|
16
|
|
|
self.locale = gettext.translation(current_script, lang_folder, languages=[in_language]) |
|
17
|
|
|
|
|
18
|
|
|
def fn_add_and_shift_column(self, local_logger, timer, input_data_frame, input_details: list): |
|
19
|
|
|
evr = 'Empty Values Replacement' |
|
20
|
|
|
for crt_dict in input_details: |
|
21
|
|
|
timer.start() |
|
22
|
|
|
input_data_frame[crt_dict['New Column']] = input_data_frame[crt_dict['Original Column']] |
|
23
|
|
|
col_offset = self.fn_set_shifting_value(crt_dict) |
|
24
|
|
|
input_data_frame[crt_dict['New Column']] = \ |
|
25
|
|
|
input_data_frame[crt_dict['New Column']].shift(col_offset) |
|
26
|
|
|
input_data_frame[crt_dict['New Column']] = \ |
|
27
|
|
|
input_data_frame[crt_dict['New Column']].apply(lambda x: str(x) |
|
28
|
|
|
.replace('nan', str(crt_dict[evr])) |
|
|
|
|
|
|
29
|
|
|
.replace('.0', '')) |
|
30
|
|
|
local_logger.info(self.locale.gettext( |
|
31
|
|
|
'A new column named "{new_column_name}" as copy from "{original_column}" ' |
|
32
|
|
|
+ 'then shifted by {shifting_rows} to relevant data frame ' |
|
33
|
|
|
+ '(filling any empty value as {empty_values_replacement})') |
|
34
|
|
|
.replace('{new_column_name}', crt_dict['New Column']) |
|
35
|
|
|
.replace('{original_column}', crt_dict['Original Column']) |
|
36
|
|
|
.replace('{shifting_rows}', str(col_offset)) |
|
37
|
|
|
.replace('{empty_values_replacement}', |
|
38
|
|
|
str(crt_dict['Empty Values Replacement']))) |
|
39
|
|
|
timer.stop() |
|
40
|
|
|
return input_data_frame |
|
41
|
|
|
|
|
42
|
|
|
@staticmethod |
|
43
|
|
|
def fn_add_minimum_and_maximum_columns_to_data_frame(input_data_frame, dict_expression): |
|
44
|
|
|
grouped_df = input_data_frame.groupby(dict_expression['group_by']) \ |
|
45
|
|
|
.agg({dict_expression['calculation']: ['min', 'max']}) |
|
46
|
|
|
grouped_df.columns = ['_'.join(col).strip() for col in grouped_df.columns.values] |
|
47
|
|
|
grouped_df = grouped_df.reset_index() |
|
48
|
|
|
if 'map' in dict_expression: |
|
49
|
|
|
grouped_df.rename(columns=dict_expression['map'], inplace=True) |
|
50
|
|
|
return grouped_df |
|
51
|
|
|
|
|
52
|
|
|
def fn_apply_query_to_data_frame(self, local_logger, timer, input_data_frame, extract_params): |
|
53
|
|
|
timer.start() |
|
54
|
|
|
query_expression = '' |
|
55
|
|
|
generic_pre_feedback = self.locale.gettext('Will retain only values {filter_type} ' |
|
56
|
|
|
+ '"{filter_values}" within the field ' |
|
57
|
|
|
+ '"{column_to_filter}"') \ |
|
58
|
|
|
.replace('{column_to_filter}', extract_params['column_to_filter']) |
|
59
|
|
|
if extract_params['filter_to_apply'] == 'equal': |
|
60
|
|
|
local_logger.debug(generic_pre_feedback |
|
61
|
|
|
.replace('{filter_type}', self.locale.gettext('equal with')) |
|
62
|
|
|
.replace('{filter_values}', extract_params['filter_values'])) |
|
63
|
|
|
query_expression = '`' + extract_params['column_to_filter'] + '` == "' \ |
|
64
|
|
|
+ extract_params['filter_values'] + '"' |
|
65
|
|
|
elif extract_params['filter_to_apply'] == 'different': |
|
66
|
|
|
local_logger.debug(generic_pre_feedback |
|
67
|
|
|
.replace('{filter_type}', self.locale.gettext('different than')) |
|
68
|
|
|
.replace('{filter_values}', extract_params['filter_values'])) |
|
69
|
|
|
query_expression = '`' + extract_params['column_to_filter'] + '` != "' \ |
|
70
|
|
|
+ extract_params['filter_values'] + '"' |
|
71
|
|
|
elif extract_params['filter_to_apply'] == 'multiple_match': |
|
72
|
|
|
multiple_values = '["' + '", "'.join(extract_params['filter_values'].values()) + '"]' |
|
73
|
|
|
local_logger.debug(generic_pre_feedback |
|
74
|
|
|
.replace('{filter_type}', |
|
75
|
|
|
self.locale.gettext('matching any of these values')) |
|
76
|
|
|
.replace('{filter_values}', multiple_values)) |
|
77
|
|
|
query_expression = '`' + extract_params['column_to_filter'] + '` in ' + multiple_values |
|
78
|
|
|
local_logger.debug(self.locale.gettext('Query expression to apply is: {query_expression}') |
|
79
|
|
|
.replace('{query_expression}', query_expression)) |
|
80
|
|
|
input_data_frame.query(query_expression, inplace=True) |
|
81
|
|
|
timer.stop() |
|
82
|
|
|
return input_data_frame |
|
83
|
|
|
|
|
84
|
|
|
def fn_filter_data_frame_by_index(self, local_logger, in_data_frame, filter_rule): |
|
85
|
|
|
reference_expression = filter_rule['Query Expression for Reference Index'] |
|
86
|
|
|
index_current = in_data_frame.query(reference_expression, inplace=False) |
|
87
|
|
|
local_logger.info(self.locale.gettext( |
|
88
|
|
|
'Current index has been determined to be {index_current_value}') |
|
89
|
|
|
.replace('{index_current_value}', str(index_current.index))) |
|
90
|
|
|
if str(index_current.index) != "Int64Index([], dtype='int64')" \ |
|
91
|
|
|
and 'Deviation' in filter_rule: |
|
92
|
|
|
in_data_frame = self.fn_filter_data_frame_by_index_internal(local_logger, { |
|
93
|
|
|
'data frame': in_data_frame, |
|
94
|
|
|
'deviation': filter_rule['Deviation'], |
|
95
|
|
|
'index': index_current.index, |
|
96
|
|
|
}) |
|
97
|
|
|
return in_data_frame |
|
98
|
|
|
|
|
99
|
|
|
def fn_filter_data_frame_by_index_internal(self, local_logger, in_dict): |
|
100
|
|
|
in_data_frame = in_dict['data_frame'] |
|
101
|
|
|
for deviation_type in in_dict['deviation']: |
|
102
|
|
|
deviation_number = in_dict['deviation'][deviation_type] |
|
103
|
|
|
index_to_apply = in_dict['index'] |
|
104
|
|
|
if deviation_type == 'Lower': |
|
105
|
|
|
index_to_apply -= deviation_number |
|
106
|
|
|
in_data_frame = in_data_frame[in_dict['index'] >= index_to_apply[0]] |
|
107
|
|
|
elif deviation_type == 'Upper': |
|
108
|
|
|
index_to_apply += deviation_number |
|
109
|
|
|
in_data_frame = in_data_frame[in_dict['index'] <= index_to_apply[0]] |
|
110
|
|
|
local_logger.info(self.locale.gettext( |
|
111
|
|
|
'{deviation_type} Deviation Number is {deviation_number} ' |
|
112
|
|
|
+ 'to be applied to Current index, became {index_to_apply}') |
|
113
|
|
|
.replace('{deviation_type}', deviation_type) |
|
114
|
|
|
.replace('{deviation_number}', str(deviation_number)) |
|
115
|
|
|
.replace('{index_to_apply}', str(index_to_apply))) |
|
116
|
|
|
return in_dict['data_frame'] |
|
117
|
|
|
|
|
118
|
|
|
@staticmethod |
|
119
|
|
|
def fn_get_column_index_from_data_frame(data_frame_columns, column_name_to_identify): |
|
120
|
|
|
column_index_to_return = 0 |
|
121
|
|
|
for ndx, column_name in enumerate(data_frame_columns): |
|
122
|
|
|
if column_name == column_name_to_identify: |
|
123
|
|
|
column_index_to_return = ndx |
|
124
|
|
|
return column_index_to_return |
|
125
|
|
|
|
|
126
|
|
|
@staticmethod |
|
127
|
|
|
def fn_get_first_and_last_column_value_from_data_frame(in_data_frame, in_column_name): |
|
128
|
|
|
return { |
|
129
|
|
|
'first': in_data_frame.iloc[0][in_column_name], |
|
130
|
|
|
'last': in_data_frame.iloc[(len(in_data_frame) - 1)][in_column_name], |
|
131
|
|
|
} |
|
132
|
|
|
|
|
133
|
|
|
@staticmethod |
|
134
|
|
|
def fn_set_shifting_value(in_dict): |
|
135
|
|
|
offset_sign = 1 |
|
136
|
|
|
if in_dict['Direction'] == 'up': |
|
137
|
|
|
offset_sign = -1 |
|
138
|
|
|
return offset_sign * in_dict['Deviation'] |
|
139
|
|
|
|
danielgp /
db-extractor
Loading history...