def drop_outliers():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
z_values = request_dict['z_values']
standard_deviation = request_dict['standard_deviation']
keys = list(z_values.keys())
vals = [z_values[x] for x in keys]
transpose_vals = pd.np.transpose(vals).tolist()
bools = []
for i in transpose_vals:
b = all(item < standard_deviation for item in i)
bools.append(b)
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
filtered_df = df[bools]
df_json = filtered_df.to_json(orient='split', date_format='iso')
response = app.response_class(response=df_json,
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def naive_bayes():
try:
request_dict = request.get_json()
traning_features = request_dict['traning_features']
traning_targets = request_dict['traning_targets']
test_features = request_dict['test_features']
from sklearn.preprocessing import StandardScaler
sc = StandardScaler()
X_train = sc.fit_transform(pd.np.array(traning_features))
X_test = sc.transform(pd.np.array(test_features))
# Fitting Naive Bayes to the Training set
from sklearn.naive_bayes import GaussianNB
classifier = GaussianNB()
classifier.fit(X_train, traning_targets)
# Predicting the Test set results
y_pred = classifier.predict(X_test)
json_response = json.dumps(y_pred.tolist())
response = app.response_class(response=json_response,
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
print(exception)
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
print(exception)
return response
def merge():
try:
request_dict = request.get_json()
left_df = request_dict['leftDf']
right_df = request_dict['rightDf']
how = request_dict['how']
left_on = request_dict['left_on']
right_on = request_dict['right_on']
left_index = request_dict['left_index']
right_index = request_dict['right_index']
left_df = pd.read_json(json.dumps(eval(left_df)), orient='split')
right_df = pd.read_json(json.dumps(eval(right_df)), orient='split')
df = left_df.merge(right_df,
how=how,
left_on=left_on,
right_on=right_on,
left_index=left_index,
right_index=right_index)
df_json = df.to_json(orient='split')
response = app.response_class(response=df_json,
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def by_contains():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
items = request_dict['item']
axis = request_dict['axis']
axis = int(axis)
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
df = df.filter(like=items, axis=axis)
if df.empty:
raise EmptyDataframe(
{
"content":
"Returned empty dataframe, check your filter index and items"
},
status_code=400)
df_json = df.to_json(orient='split')
response = app.response_class(response=df_json,
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def by_dict():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
df = pd.DataFrame(eval(jsonstr))
df_json = df.to_json(orient='split')
response = app.response_class(response=df_json,
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def describe():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
dataframe_describe = df.describe(include='all')
df_json = dataframe_describe.to_json(orient='split', date_format='iso')
response = app.response_class(response=df_json,
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def by_bool_expression():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
expression = request_dict['boolExpression']
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
selected_rows = eval(expression)
df_json = selected_rows.to_json(orient='split', date_format='iso')
response = app.response_class(response=df_json,
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def by_label():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
row_label = request_dict['rowLabel']
column_label = request_dict['columnLabel']
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
selected_rows = df.loc[row_label, column_label]
df_json = selected_rows.to_json(orient='split', date_format='iso')
response = app.response_class(response=df_json,
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def by_contains():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
column = request_dict['column']
contains_str = request_dict['containsString']
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
selected_rows = df[df[column].str.contains(contains_str, na=False)]
df_json = selected_rows.to_json(orient='split', date_format='iso')
response = app.response_class(response=df_json,
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def tabulate():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
jsonstr = json.dumps(jsonstr)
df = pd.read_json(eval(jsonstr), orient='split')
headers = 'keys'
tableformat = 'orgtbl'
tabulated_df = tb(df, headers=headers, tablefmt=tableformat)
response = app.response_class(response=tabulated_df,
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def min_value():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
dataframe_min_value = df.min()
values = dataframe_min_value.values.tolist()
keys = dataframe_min_value.index.values.tolist()
min_value_dict = dict(zip(keys, values))
response = app.response_class(response=json.dumps(min_value_dict),
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def cumulative_sum():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
dataframe_cumsum = df.cumsum()
values = list(map(list, zip(*dataframe_cumsum.values.tolist())))
keys = dataframe_cumsum.columns.values.tolist()
cum_dict = dict(zip(keys, values))
response = app.response_class(response=json.dumps(cum_dict),
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def shape():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
dataframe_shape = df.shape
response = app.response_class(
response=json.dumps(dataframe_shape),
status=200,
mimetype='application/json'
)
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(
response=exception,
status=400,
mimetype='application/json'
)
return response
def sum():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
axis = request_dict['axis']
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
dataframe_sum = df.sum(axis=axis, skipna=True)
values = dataframe_sum.values.tolist()
keys = dataframe_sum.index.values.tolist()
sum_dict = dict(zip(keys, values))
response = app.response_class(response=json.dumps(sum_dict),
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def by_excel():
try:
request_dict = request.get_json()
file_path = request_dict['filePath']
sheet_name = request_dict['sheetName']
df = pd.read_excel(file_path,
sheet_name=sheet_name,
header=0,
na_values=['', ' '])
df_json = df.to_json(orient='split', date_format='iso')
response = app.response_class(response=df_json,
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def index():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
dataframe_index = {"index":df.index.values.tolist(),"dtype":str(df.index.dtype)}
response = app.response_class(
response=json.dumps(dataframe_index),
status=200,
mimetype='application/json'
)
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(
response=exception,
status=400,
mimetype='application/json'
)
return response
def info():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
buf = io.StringIO()
dataframe_info = df.info(buf=buf)
response = app.response_class(
response=buf.getvalue(),
status=200,
mimetype='application/json'
)
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(
response=exception,
status=400,
mimetype='application/json'
)
return response
def by_datatype():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
include = request_dict['include']
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
selected_columns = df.select_dtypes(include=include)
df_json = selected_columns.to_json(orient='split', date_format='iso')
response = app.response_class(
response=df_json,
status=200,
mimetype='application/json'
)
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(
response=exception,
status=400,
mimetype='application/json'
)
return response
def max_index_value():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
axis = request_dict['axis']
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
df = df.select_dtypes(exclude=['object'])
dataframe_max_index_value = df.idxmax(axis=axis, skipna=True)
values = dataframe_max_index_value.values.tolist()
keys = dataframe_max_index_value.index.values.tolist()
max_index_value_dict = dict(zip(keys, values))
response = app.response_class(
response=json.dumps(max_index_value_dict),
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def concatenate():
try:
request_dict = request.get_json()
df_json_list = request_dict['df_json_list']
axis = request_dict['axis']
join = request_dict['join']
ignore_index = request_dict['ignore_index']
df_list = []
for i in df_json_list:
df_list.append(pd.read_json(json.dumps(eval(i)), orient='split'))
df = pd.concat(df_list, axis=axis, ignore_index=ignore_index)
df_json = df.to_json(orient='split')
response = app.response_class(response=df_json,
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
def count():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
from scipy import stats
dataframe_count = df.count()
count_dict = dict(zip(dataframe_count.index.values.tolist(), dataframe_count.values.tolist()))
response = app.response_class(
response=json.dumps(count_dict),
status=200,
mimetype='application/json'
)
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(
response=exception,
status=400,
mimetype='application/json'
)
return response
def z_score():
try:
request_dict = request.get_json()
jsonstr = request_dict['jsonStr']
columns = request_dict['columns']
df = pd.read_json(json.dumps(eval(jsonstr)), orient='split')
if (columns is None):
z_values = pd.np.abs(stats.zscore(df))
z_values = pd.np.transpose(z_values)
result = dict(zip(df.columns.values.tolist(), z_values.tolist()))
else:
z_values = pd.np.abs(stats.zscore(df[columns]))
z_values = pd.np.transpose(z_values)
result = dict(zip(columns, z_values.tolist()))
print(result)
response = app.response_class(response=json.dumps(result),
status=200,
mimetype='application/json')
except:
exception = ExceptionHelpers.format_exception(sys.exc_info())
response = app.response_class(response=exception,
status=400,
mimetype='application/json')
return response
