def __call__(self, df):
if len(self.args) >= 2:
if not isinstance(self.args[0], dplython.later.Later) or \
not isinstance(self.args[1], dplython.later.Later):
raise ValueError(
"Arguments must be of the form \"X.column1, X.column2, ...\""
)
sp_key = self.args[0]._name
sp_value = self.args[1]._name
else:
raise ValueError(
"You must provide at least two arguments, the key and the value."
)
all_id_cols = []
all_value_cols = list(df.columns)
if len(self.args) > 2:
if 'exclude' in self.kwargs and self.kwargs['exclude'] == True:
for arg in self.args[2:]:
if not isinstance(arg, dplython.later.Later):
raise ValueError(
"Arguments must be of the form \"X.column1, X.column2, ...\""
)
all_id_cols.append(arg._name)
all_value_cols.remove(arg._name)
else:
all_id_cols = list(df.columns)
all_value_cols = []
for arg in self.args[2:]:
if not isinstance(arg, dplython.later.Later):
raise ValueError(
"Arguments must be of the form \"X.column1, X.column2, ...\""
)
all_id_cols.remove(arg._name)
all_value_cols.append(arg._name)
outdf = DplyFrame(
df.melt(id_vars=all_id_cols, value_vars=all_value_cols))
cols = list(outdf.columns)
cols[-2:] = sp_key, sp_value
outdf.columns = cols
return outdf
def read_delim(f, delim, col_names = True):
assert isinstance(f, str)
assert isinstance(delim, str)
assert isinstance(col_names, bool)
if col_names == True:
col_names = 0
else:
col_names = None
df = DplyFrame(pd.read_csv(filepath_or_buffer=f, header=col_names, sep=delim))
if col_names == None:
df.columns = [''.join(map(str, list(n))) for n in zip(cycle(['X']), range(1, df.shape[1]+1))]
return df