import matplotlib.pyplot as plt
from .figure import Figure, inherit_split_depth
from ..fun.misc import reduce_list as rl
[docs]
class Simple(Figure):
"""Scatter plot of columns from a Table.
Args:
reqs[0] (Table): Table containing X and Y axes to create Figure.
param["calc_cols"] (list of str): Column names for X and Y axes.
param["marker_styles"] (str or list of str, optional): Marker style of
each group. Defaults to "o".
param["group_depth"] (int): Data split depth number.
Returns:
Figure: matplotlib Figure object
"""
[docs]
def set_info(self, param={}):
"""Copy info from reqs[0] and add params.
"""
self.info.copy_req(0)
inherit_split_depth(self, 0, param["group_depth"])
self.info.add_param(
"calc_cols", param["calc_cols"], "str", "X and Y columns")
self.info.add_param(
"marker_styles", param.get("marker_styles", "o"), "list of str",
"Marker style of each group")
[docs]
@staticmethod
def process(reqs, param):
"""Scatter plot of columns from a table.
Args:
reqs[0] (pandas.DataFrame): Table containing X and Y axes to create
figure.
param["calc_cols"] (list of str): Column names for X and Y axes.
param["marker_styles"] (str or list of str, optional): Marker style
of each group. Defaults to "o".
param["index_cols"] (list of str): Column names of index.
These column names are used for
:meth:`pandas.DataFrame.groupby`.
Returns:
matplotlib.figure.Figure: matplotlib Figure containing scatter plot
"""
df = reqs[0].copy()
fig, ax = plt.subplots()
if len(param["index_cols"]) == 0:
x = df[param["calc_cols"][0]].values
y = df[param["calc_cols"][1]].values
ax.scatter(x, y, label="scatter", marker=param["marker_styles"])
else:
for i, (_, row) in enumerate(df.groupby(rl(param["index_cols"]))):
x = row[param["calc_cols"][0]].values
y = row[param["calc_cols"][1]].values
if type(param["marker_styles"]) == str:
ax.scatter(x, y, marker=param["marker_styles"],
label="scatter" + str(i + 1))
else:
ax.scatter(x, y, marker=param["marker_styles"][i],
label="scatter" + str(i + 1))
return fig