convert ngram data to csv format

backend/download/create_csv.py

@@ -108,4 +108,21 @@ def format_field_value(value, unit):
             'week': '%Y-%m-%d',
             'day': '%Y-%m-%d'
         }
-        return date.strftime(formats[unit])
+        return 
+
+def ngram_csv(results, filename):
+    rows = ngram_table(results)
+    fieldnames = ['date', 'N-gram', 'Frequency']
+    filepath = write_file(filename, fieldnames, rows)
+    return filepath
+
+def ngram_table(results):
+    rows = []
+    for index, time_point in enumerate(results['time_points']):
+        for ngram in results['words']:
+            rows.append({
+                'date': time_point,
+                'N-gram': ngram['label'],
+                'Frequency': ngram['data'][index]
+            })
+    return rows

backend/download/tasks.py

@@ -90,10 +90,12 @@ def download_search_results(request_json, user):
     return try_download(make_chain, download)
 
 @shared_task()
-def make_term_frequency_csv(results_per_series, parameters_per_series):
+def make_full_data_csv(results_per_series, visualization_type, parameters_per_series):
     '''
     Export term frequency results to a csv.
     '''
+    if visualization_type == 'ngram':
+        return create_csv.ngram_csv(results_per_series)
     query_per_series, field_name, unit = extract_term_frequency_download_metadata(parameters_per_series)
     return create_csv.term_frequency_csv(query_per_series, results_per_series, field_name, unit = unit)
 
@@ -170,7 +172,7 @@ def download_full_data(request_json, user):
 
     make_chain = lambda : chain(
         task,
-        make_term_frequency_csv.s(parameters),
+        make_full_data_csv.s(visualization_type, parameters),
         complete_download.s(download.id),
         csv_data_email.s(user.email, user.username),
     ).on_error(complete_failed_download.s(download.id))

backend/download/tests/test_csv_results.py

@@ -208,3 +208,26 @@ def test_date_format():
 
     for value, unit, expected in cases:
         assert create_csv.format_field_value(value, unit) == expected
+
+
+mock_ngram_data = {
+    'words': [
+        {'label': 'ex parrot', 'data': [2, 3]},
+        {'label': 'this parrot what', 'data': [4, 8]},
+        {'label': 'dead parrot when', 'data': [4, 6]},
+    ],
+    'time_points': ['1960-1965', '1962-1967']
+}
+
+expected_csv_table = [
+    {'date': '1960-1965', 'N-gram': 'ex parrot', 'Frequency': 2},
+    {'date': '1960-1965', 'N-gram': 'this parrot what', 'Frequency': 4},
+    {'date': '1960-1965', 'N-gram': 'dead parrot when', 'Frequency': 4},
+    {'date': '1962-1967', 'N-gram': 'ex parrot', 'Frequency': 3},
+    {'date': '1962-1967', 'N-gram': 'this parrot what', 'Frequency': 8},
+    {'date': '1962-1967', 'N-gram': 'dead parrot when', 'Frequency': 6},
+]
+
+def test_ngram_table():
+    table = create_csv.ngram_table(mock_ngram_data)
+    assert table == expected_csv_table