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Fixed insert last known value when df is empty bug

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l_samenv
2024-08-28 08:46:53 +02:00
parent aaefde93f9
commit d81f2024ec
1 changed files with 25 additions and 15 deletions
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40
influxdb.py
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@ -166,8 +166,6 @@ class InfluxDataGetter:
variable_name_for_query = var_param[0]
parameter = "value" if len(var_param) == 1 else var_param[1]
variables_info[variable] = {}
variables_info[variable]["expired_ranges"] = []
query = f"""
from(bucket: "{self._bucket}")
|> range(start: {times[0]}, stop: {times[1] + 1})
@ -202,16 +200,26 @@ class InfluxDataGetter:
row_to_insert = row
except:
row_to_insert = row
try:
try: #row_to_insert might be None
if not row_to_insert.empty :
row_to_insert["timestamp"] = float(times[0])
data_frame.loc[-1] = row_to_insert
if data_frame.empty:
data_frame = row_to_insert.to_frame().T
else:
data_frame.loc[-1] = row_to_insert
except:
pass
if data_frame.empty:
continue
data_frame.drop(["result", "table"], axis=1, inplace=True)
data_frame.sort_values(by=["timestamp"], inplace=True)
data_frame.reset_index()
variables_info[variable] = {}
variables_info[variable]["expired_ranges"] = []
# Identify time windows for which the curve is expired
for index, row in data_frame.iterrows():
@ -225,25 +233,27 @@ class InfluxDataGetter:
data_frame.drop(["expired"], axis=1, inplace=True)
variables_info[variable]["df"] = data_frame
res = None
non_empty_variables = list(variables_info.keys())
# Merge single curve dataframes to a global one
if len(variables) == 1:
res = variables_info[variables[0]]["df"]
elif len(variables) == 2:
res = merge_ordered(variables_info[variables[0]]["df"], variables_info[variables[1]]["df"], on=["timestamp", "relative"], suffixes=(None, None))
if len(non_empty_variables) == 0:
return df()
elif len(non_empty_variables) == 1:
res = variables_info[non_empty_variables[0]]["df"]
else :
for i,variable in enumerate(variables):
for i in range(0, len(non_empty_variables)):
if i == 1:
res = merge_ordered(variables_info[variables[0]]["df"], variables_info[variables[1]]["df"], on=["timestamp", "relative"], suffixes=(None, None))
res = merge_ordered(variables_info[non_empty_variables[0]]["df"], variables_info[non_empty_variables[1]]["df"], on=["timestamp", "relative"], suffixes=(None, None))
elif i > 1:
res = merge_ordered(res, variables_info[variables[i]]["df"], on=["timestamp", "relative"], suffixes=(None, None))
res = merge_ordered(res, variables_info[non_empty_variables[i]]["df"], on=["timestamp", "relative"], suffixes=(None, None))
# Forward fill missing values, then set data points to NaN for those which are expired
if len(variables) > 1:
if len(non_empty_variables) > 1:
res.ffill(inplace=True)
for variable, info in variables_info.items():
for range in info["expired_ranges"]:
res.loc[(res["timestamp"] >= range[0]) & ((res["timestamp"] < range[1]) if len(range) == 2 else True), variable] = NaN
for expired_range in info["expired_ranges"]:
res.loc[(res["timestamp"] >= expired_range[0]) & ((res["timestamp"] < expired_range[1]) if len(expired_range) == 2 else True), variable] = NaN
# Change order of columns
cols = res.columns.tolist()