def percent(dataframe: hint.dataframe) -> None:
"""
Add percent resist column
Args:
dataframe: dataframe to process
Effects:
add percent column
"""
def resist(row) -> float:
"""
Percent resistant of row value
Args:
row: row of dataframe
Returns:
percent resistant
"""
ss = row['genotype_susceptible']
sr = row['genotype_heterozygous']
rr = row['genotype_resistant']
total = 2 * (ss + sr + rr)
if total == 0:
return np.nan
else:
r = 2 * rr + sr
return r / total
dataframe['percent'] = dataframe.apply(lambda row: resist(row), axis=1)
def _cut_dataframe(dataframe: hint.dataframe) -> hint.dataframe:
"""
Cut the dataframe to start at the new point
Args:
dataframe: dataframe to cut
Returns:
the cut dataframe
"""
new = dataframe.copy()
new = new.iloc[start_point:]
new.reset_index(inplace=True, drop=True)
return new
def cut_dataframe(self, dataframe: hint.dataframe) -> hint.dataframe:
"""
Cut dataframe to start at new point
Args:
dataframe: dataframe to cut
Returns:
the cut dataframe
"""
new = dataframe.copy()
new = new.iloc[self.cut_point:]
new.reset_index(inplace=True, drop=True)
new['index'] = range(len(new.index))
return new
def percent_dataframe(dataframe: hint.dataframe) -> None:
"""
Add percent resist column
Args:
dataframe: dataframe to process
Effects:
add percent column
"""
def resist(row) -> float:
"""
Percent resistant of row value
Args:
row: row of dataframe
Returns:
percent resistant
"""
ss = row[runs.columns[2]]
sr = row[runs.columns[1]]
rr = row[runs.columns[0]]
total = 2 * (ss + sr + rr)
if total == 0:
return np.nan
else:
r = 2 * rr + sr
return r / total
dataframe['new'] \
= dataframe.apply(lambda row: resist(row), axis=1)
def ratios(dataframe: hint.dataframe) -> None:
"""
Add ratio of genotype columns
Args:
dataframe: dataframe to process
Effects:
add ratio columns
"""
def resist(row) -> float:
"""
Percent resistant of row value
Args:
row: row of dataframe
Returns:
percent resistant
"""
ss = row['genotype_susceptible']
sr = row['genotype_heterozygous']
rr = row['genotype_resistant']
total = ss + sr + rr
if total == 0:
return 0
else:
return rr / total
def suscept(row) -> float:
"""
Percent susceptible of row value
Args:
row: row of dataframe
Returns:
percent resistant
"""
ss = row['genotype_susceptible']
sr = row['genotype_heterozygous']
rr = row['genotype_resistant']
total = ss + sr + rr
if total == 0:
return 0
else:
return ss / total
def hetero(row) -> float:
"""
Percent hetero of row value
Args:
row: row of dataframe
Returns:
percent resistant
"""
ss = row['genotype_susceptible']
sr = row['genotype_heterozygous']
rr = row['genotype_resistant']
total = ss + sr + rr
if total == 0:
return 0
else:
return sr / total
dataframe['percent_resist'] = \
dataframe.apply(lambda row: resist(row), axis=1)
dataframe['percent_suscept'] = \
dataframe.apply(lambda row: suscept(row), axis=1)
dataframe['percent_hetero'] = \
dataframe.apply(lambda row: hetero(row), axis=1)