def map_query(table, compare, filter, groupby, field, agg):
global DFRAMES
filter = ".query('%s')" % filter if filter != "empty" else ""
df_main = DFRAMES['main']
df_alt = DFRAMES['alternative']
if compare=='Main vs. Alternative':
print 'Showing base-alternative comparison'
if field not in df_main.columns:
print "Col not found, trying eval:", field
df_main["eval"] = df_main.eval(field)
field = "eval"
cmd_base = "df_main%s.groupby('%s')['%s'].%s" % \
(filter, groupby, field, agg)
print cmd_base
if field not in df_alt.columns:
print "Col not found, trying eval:", field
df_alt["eval"] = df_alt.eval(field)
field = "eval"
cmd_alt = "df_alt%s.groupby('%s')['%s'].%s" % \
(filter, groupby, field, agg)
base_results = eval(cmd_base)
base_results[base_results == np.inf] = np.nan
alt_results = eval(cmd_alt)
alt_results[alt_results == np.inf] = np.nan
# Percent change versus base, should be flexible in future
results = (alt_results-base_results)/base_results
else:
print 'Showing primary results'
if field not in df_main.columns:
df_main["eval"] = df_main.eval(field)
field = "eval"
cmd_base = "df_main%s.groupby('%s')['%s'].%s" % \
(filter, groupby, field, agg)
results = eval(cmd_base)
results = yamlio.series_to_yaml_safe(results.dropna())
results = {int(k): results[k] for k in results}
return results
def map_query(table, compare, filter, groupby, field, agg):
global DFRAMES
filter = ".query('%s')" % filter if filter != "empty" else ""
df_main = DFRAMES['main']
df_alt = DFRAMES['alternative']
if compare=='Main vs. Alternative':
print 'Showing base-alternative comparison'
if field not in df_main.columns:
print "Col not found, trying eval:", field
df_main["eval"] = df_main.eval(field)
field = "eval"
cmd_base = "df_main%s.groupby('%s')['%s'].%s" % \
(filter, groupby, field, agg)
print cmd_base
if field not in df_alt.columns:
print "Col not found, trying eval:", field
df_alt["eval"] = df_alt.eval(field)
field = "eval"
cmd_alt = "df_alt%s.groupby('%s')['%s'].%s" % \
(filter, groupby, field, agg)
base_results = eval(cmd_base)
base_results[base_results == np.inf] = np.nan
alt_results = eval(cmd_alt)
alt_results[alt_results == np.inf] = np.nan
# Percent change versus base, should be flexible in future
results = (alt_results-base_results)/base_results
else:
print 'Showing primary results'
if field not in df_main.columns:
df_main["eval"] = df_main.eval(field)
field = "eval"
cmd_base = "df_main%s.groupby('%s')['%s'].%s" % \
(filter, groupby, field, agg)
results = eval(cmd_base)
results = yamlio.series_to_yaml_safe(results.dropna())
results = {int(k): results[k] for k in results}
return results
def map_query(table, filter, groupby, field, agg):
global DFRAMES
filter = ".query('%s')" % filter if filter != "empty" else ""
df = DFRAMES[table]
if field not in df.columns:
print "Col not found, trying eval:", field
df["eval"] = df.eval(field)
field = "eval"
cmd = "df%s.groupby('%s')['%s'].%s" % \
(filter, groupby, field, agg)
print cmd
results = eval(cmd)
results[results == np.inf] = np.nan
results = yamlio.series_to_yaml_safe(results.dropna())
results = {int(k): results[k] for k in results}
return results
def map_query(table, filter, groupby, field, agg):
global DFRAMES
filter = ".query('%s')" % filter if filter != "empty" else ""
df = DFRAMES[table]
if field not in df.columns:
print "Col not found, trying eval:", field
df["eval"] = df.eval(field)
field = "eval"
cmd = "df%s.groupby('%s')['%s'].%s" % \
(filter, groupby, field, agg)
print cmd
results = eval(cmd)
results[results == np.inf] = np.nan
results = yamlio.series_to_yaml_safe(results.dropna())
results = {int(k): results[k] for k in results}
return results
