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compare two dfs, small bugs but logic is now there

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Signed-off-by: Dipti <dipti.dhond@candelatech.com>
This commit is contained in:
Dipti
2021-02-25 09:38:48 -08:00
parent 7d03848c90
commit dcf85ba785
2 changed files with 71 additions and 12 deletions
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81
py-json/LANforge/lfcli_base.py
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@@ -662,20 +662,79 @@ class LFCliBase:
if file_name.split('.')[-1] == 'csv':
return pd.read_csv(file_name)
#only works for test_ipv4_variable_time at the moment
def compare_two_df(self,dataframe_one=None,dataframe_two=None):
#df one = current report
#df two = compared report
pd.set_option("display.max_rows", None, "display.max_columns", None)
#get all of common columns besides Timestamp, Timestamp milliseconds
common_cols = set(dataframe_one.columns).intersection(set(dataframe_two.columns))
if common_cols is not None:
cols_to_remove=['Timestamp milliseconds epoch','Timestamp','LANforge GUI Build: 5.4.3']
#drop unwanted cols from df
dataframe_one = dataframe_one.drop(list(cols_to_remove), axis=1)
dataframe_two = dataframe_two.drop(list(cols_to_remove), axis=1)
#for time elapsed section and endpoint name combo
#
#print(dataframe_one)
#print(dataframe_two)
common_cols = list(set(dataframe_one.columns).intersection(set(dataframe_two.columns)))
cols_to_remove = ['Timestamp milliseconds epoch','Timestamp','LANforge GUI Build: 5.4.3']
com_cols = [i for i in common_cols if i not in cols_to_remove]
#check if dataframes have the same endpoints
if dataframe_one.name.unique().tolist().sort() == dataframe_two.name.unique().tolist().sort():
endpoint_names = dataframe_one.name.unique().tolist()
if com_cols is not None:
dataframe_one = dataframe_one[[c for c in dataframe_one.columns if c in com_cols]]
dataframe_two = dataframe_two[[c for c in dataframe_one.columns if c in com_cols]]
dataframe_one = dataframe_one.loc[:, ~dataframe_one.columns.str.startswith('Script Name:')]
dataframe_two = dataframe_two.loc[:, ~dataframe_two.columns.str.startswith('Script Name:')]
lowest_duration=min(dataframe_one['Duration elapsed'].max(),dataframe_two['Duration elapsed'].max())
print("The max duration in the new dataframe will be... " + str(lowest_duration))
compared_values_dataframe = pd.DataFrame(columns=[col for col in com_cols if not col.startswith('Script Name:')])
cols = compared_values_dataframe.columns.tolist()
cols=sorted(cols, key=lambda L: (L.lower(), L))
compared_values_dataframe= compared_values_dataframe[cols]
print(compared_values_dataframe)
for duration_elapsed in range(lowest_duration):
for endpoint in endpoint_names:
#check if value has a space in it or is a str.
# if value as a space, only take value before space for calc, append that calculated value after space.
#if str. check if values match from 2 df's. if values do not match, write N/A
for_loop_df1 = dataframe_one.loc[(dataframe_one['name'] == endpoint) & (dataframe_one['Duration elapsed'] == duration_elapsed)]
for_loop_df2 = dataframe_two.loc[(dataframe_one['name'] == endpoint) & (dataframe_two['Duration elapsed'] == duration_elapsed)]
# print(for_loop_df1)
# print(for_loop_df2)
cols_to_loop = [i for i in com_cols if i not in ['Duration elapsed', 'Name', 'Script Name: test_ipv4_variable_time']]
cols_to_loop=sorted(cols_to_loop, key=lambda L: (L.lower(), L))
print(cols_to_loop)
row_to_append={}
row_to_append["Duration elapsed"] = duration_elapsed
for col in cols_to_loop:
print(col)
print(for_loop_df1)
#print(for_loop_df2)
print(for_loop_df1.at[0, col])
print(for_loop_df2.at[0, col])
if type(for_loop_df1.at[0, col]) == str and type(for_loop_df2.at[0, col]) == str:
if (' ' in for_loop_df1.at[0,col]) == True:
#do subtraction
new_value = float(for_loop_df1.at[0, col].split(" ")[0]) - float(for_loop_df2.at[0, col].split(" ")[0])
#add on last half of string
new_value = str(new_value)+ for_loop_df2.at[0, col].split(" ")[1]
# print(new_value)
row_to_append[col] = new_value
else:
if for_loop_df1.at[0, col] != for_loop_df2.at[0, col]:
row_to_append[col] = 'NaN'
else:
row_to_append[col] = for_loop_df1.at[0,col]
elif type(for_loop_df1.at[0, col]) == int and type(for_loop_df2.at[0, col]) == int or type(for_loop_df1.at[0, col]) == float and type(for_loop_df2.at[0,col]) == float:
new_value = for_loop_df1.at[0, col] - for_loop_df2.at[0, col]
row_to_append[col] = new_value
compared_values_dataframe = compared_values_dataframe.append(row_to_append, ignore_index=True,)
print(compared_values_dataframe)
#add col name to new df
print(dataframe_one)
print(dataframe_two)
print(compared_values_dataframe)
else:
ValueError("Unable to execute report comparison due to inadequate file commonalities. ")
exit(1)
else:
ValueError("Two files do not have the same endpoints. Please try file comparison with files that have the same endpoints.")
exit(1)
#take those columns and separate those columns from others in DF.