使用 seaborn 包的具有三个 y 轴的嵌套条形图
Nested bar plots with three y axis using seaborn package
使用 python seaborn 包,我试图绘制具有三个不同 y 轴的嵌套条形图,如下图所示:
我使用的代码是:
import matplotlib.pyplot as plt
from matplotlib import rc
import numpy as np
import seaborn as sns
#plt.style.use(['science'])
rc('font', **{'family': 'serif', 'serif': ['Computer Modern']})
rc('text', usetex=True)
HV = [388, 438]
YS = [1070, 1200]
UTS = [1150, 1400]
Z = [15, 12.5]
x = [1, 2]
fig, ax1 = plt.subplots(figsize=(5, 5.5))
colors=sns.color_palette("rocket",4)
ax1 = sns.barplot(x[0],YS[0],color="blue")
ax1 = sns.barplot(x[0],color="blue")
ax1 = sns.barplot(x[1],YS[1],color="blue")
ax1 = sns.barplot(x[1],UTS[1],color="blue")
ax2 = ax1.twinx()
ax2 = sns.barplot(x[0], HV[0],color="green")
ax2 = sns.barplot(x[1], HV[1],color="green")
ax3 = ax1.twinx()
ax3 = sns.barplot(x[0],Z[0],color="red")
ax3 = sns.barplot(x[1],Z[1],color="red")
#ax3.spines['right'].set_position(('outward',60))
ax3.spines['right'].set_position(('axes',1.15))
ax1.set_ylabel("First",color="blue")
ax2.set_ylabel("Second",color="green")
ax3.set_ylabel("Third",color="red")
ax1.tick_params(axis='y',colors="blue")
ax2.tick_params(axis='y',colors="green")
ax3.tick_params(axis='y',colors="red")
ax2.spines['right'].set_color("green")
ax3.spines['right'].set_color("red")
ax3.spines['left'].set_color("blue")
plt.show()
我收到以下错误:
Traceback (most recent call last):
File "/usr/lib/python3/dist-packages/seaborn/utils.py", line 531, in categorical_order
order = values.cat.categories
AttributeError: 'int' object has no attribute 'cat'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/lib/python3/dist-packages/seaborn/utils.py", line 534, in categorical_order
order = values.unique()
AttributeError: 'int' object has no attribute 'unique'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/sspenkulinti/these/thesis_E185_fatigue/test_matrix/E185_properties_AB_HT.py", line 21, in <module>
ax1 = sns.barplot(x[0],YS[0],color="blue")
File "/usr/lib/python3/dist-packages/seaborn/categorical.py", line 3147, in barplot
plotter = _BarPlotter(x, y, hue, data, order, hue_order,
File "/usr/lib/python3/dist-packages/seaborn/categorical.py", line 1614, in __init__
self.establish_variables(x, y, hue, data, orient,
File "/usr/lib/python3/dist-packages/seaborn/categorical.py", line 200, in establish_variables
group_names = categorical_order(groups, order)
File "/usr/lib/python3/dist-packages/seaborn/utils.py", line 536, in categorical_order
order = pd.unique(values)
File "/usr/lib/python3/dist-packages/pandas/core/algorithms.py", line 395, in unique
values = _ensure_arraylike(values)
File "/usr/lib/python3/dist-packages/pandas/core/algorithms.py", line 204, in _ensure_arraylike
inferred = lib.infer_dtype(values, skipna=False)
File "pandas/_libs/lib.pyx", line 1251, in pandas._libs.lib.infer_dtype
TypeError: 'int' object is not iterable
错误是因为您无法使用单个数字作为第一个参数调用 sns.barplot
。 x-values 需要是一个列表。
要使用 seaborn 获得所需的数据,数据需要像来自数据框一样呈现。 hue_order
需要为每个条保留足够的 space,即使那里没有绘制任何东西。
import matplotlib.pyplot as plt
from matplotlib import rc
import numpy as np
import seaborn as sns
HV = [388, 438]
YS = [1070, 1200]
UTS = [1150, 1400]
Z = [15, 12.5]
x = ["As built", "200ºC-850ºC"]
names = ['YS', 'UTS', 'HV', 'Z']
fig, ax1 = plt.subplots(figsize=(9, 5.5))
colors = sns.color_palette("tab10", len(names))
sns.barplot(x=x + x, y=YS + UTS, hue=[names[0]] * len(x) + [names[1]] * len(x),
hue_order=names, palette=colors, alpha=0.7, ax=ax1)
# ax1 will already contain the full legend, the third handle needs to
# be updated to show the hatching
ax1.legend_.legendHandles[2].set_hatch('///')
ax2 = ax1.twinx()
sns.barplot(x=x, y=HV, hue=[names[2]] * len(x), hue_order=names, palette=colors, hatch='//', alpha=0.7, ax=ax2)
ax2.legend_.remove() # seaborn automatically creates a new legend
ax3 = ax1.twinx()
sns.barplot(x=x, y=Z, hue=[names[3]] * len(x), hue_order=names, palette=colors, alpha=0.7, ax=ax3)
ax3.legend_.remove()
ax3.spines['right'].set_position(('axes', 1.15))
ax1.set_ylabel("First", color=colors[0])
ax2.set_ylabel("Second", color=colors[2])
ax3.set_ylabel("Third", color=colors[3])
ax1.tick_params(axis='y', colors=colors[0])
ax2.tick_params(axis='y', colors=colors[2])
ax3.tick_params(axis='y', colors=colors[3])
ax2.spines['right'].set_color(colors[2])
ax3.spines['right'].set_color(colors[3])
plt.tight_layout()
plt.show()
使用 python seaborn 包,我试图绘制具有三个不同 y 轴的嵌套条形图,如下图所示:
我使用的代码是:
import matplotlib.pyplot as plt
from matplotlib import rc
import numpy as np
import seaborn as sns
#plt.style.use(['science'])
rc('font', **{'family': 'serif', 'serif': ['Computer Modern']})
rc('text', usetex=True)
HV = [388, 438]
YS = [1070, 1200]
UTS = [1150, 1400]
Z = [15, 12.5]
x = [1, 2]
fig, ax1 = plt.subplots(figsize=(5, 5.5))
colors=sns.color_palette("rocket",4)
ax1 = sns.barplot(x[0],YS[0],color="blue")
ax1 = sns.barplot(x[0],color="blue")
ax1 = sns.barplot(x[1],YS[1],color="blue")
ax1 = sns.barplot(x[1],UTS[1],color="blue")
ax2 = ax1.twinx()
ax2 = sns.barplot(x[0], HV[0],color="green")
ax2 = sns.barplot(x[1], HV[1],color="green")
ax3 = ax1.twinx()
ax3 = sns.barplot(x[0],Z[0],color="red")
ax3 = sns.barplot(x[1],Z[1],color="red")
#ax3.spines['right'].set_position(('outward',60))
ax3.spines['right'].set_position(('axes',1.15))
ax1.set_ylabel("First",color="blue")
ax2.set_ylabel("Second",color="green")
ax3.set_ylabel("Third",color="red")
ax1.tick_params(axis='y',colors="blue")
ax2.tick_params(axis='y',colors="green")
ax3.tick_params(axis='y',colors="red")
ax2.spines['right'].set_color("green")
ax3.spines['right'].set_color("red")
ax3.spines['left'].set_color("blue")
plt.show()
我收到以下错误:
Traceback (most recent call last):
File "/usr/lib/python3/dist-packages/seaborn/utils.py", line 531, in categorical_order
order = values.cat.categories
AttributeError: 'int' object has no attribute 'cat'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/lib/python3/dist-packages/seaborn/utils.py", line 534, in categorical_order
order = values.unique()
AttributeError: 'int' object has no attribute 'unique'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/sspenkulinti/these/thesis_E185_fatigue/test_matrix/E185_properties_AB_HT.py", line 21, in <module>
ax1 = sns.barplot(x[0],YS[0],color="blue")
File "/usr/lib/python3/dist-packages/seaborn/categorical.py", line 3147, in barplot
plotter = _BarPlotter(x, y, hue, data, order, hue_order,
File "/usr/lib/python3/dist-packages/seaborn/categorical.py", line 1614, in __init__
self.establish_variables(x, y, hue, data, orient,
File "/usr/lib/python3/dist-packages/seaborn/categorical.py", line 200, in establish_variables
group_names = categorical_order(groups, order)
File "/usr/lib/python3/dist-packages/seaborn/utils.py", line 536, in categorical_order
order = pd.unique(values)
File "/usr/lib/python3/dist-packages/pandas/core/algorithms.py", line 395, in unique
values = _ensure_arraylike(values)
File "/usr/lib/python3/dist-packages/pandas/core/algorithms.py", line 204, in _ensure_arraylike
inferred = lib.infer_dtype(values, skipna=False)
File "pandas/_libs/lib.pyx", line 1251, in pandas._libs.lib.infer_dtype
TypeError: 'int' object is not iterable
错误是因为您无法使用单个数字作为第一个参数调用 sns.barplot
。 x-values 需要是一个列表。
要使用 seaborn 获得所需的数据,数据需要像来自数据框一样呈现。 hue_order
需要为每个条保留足够的 space,即使那里没有绘制任何东西。
import matplotlib.pyplot as plt
from matplotlib import rc
import numpy as np
import seaborn as sns
HV = [388, 438]
YS = [1070, 1200]
UTS = [1150, 1400]
Z = [15, 12.5]
x = ["As built", "200ºC-850ºC"]
names = ['YS', 'UTS', 'HV', 'Z']
fig, ax1 = plt.subplots(figsize=(9, 5.5))
colors = sns.color_palette("tab10", len(names))
sns.barplot(x=x + x, y=YS + UTS, hue=[names[0]] * len(x) + [names[1]] * len(x),
hue_order=names, palette=colors, alpha=0.7, ax=ax1)
# ax1 will already contain the full legend, the third handle needs to
# be updated to show the hatching
ax1.legend_.legendHandles[2].set_hatch('///')
ax2 = ax1.twinx()
sns.barplot(x=x, y=HV, hue=[names[2]] * len(x), hue_order=names, palette=colors, hatch='//', alpha=0.7, ax=ax2)
ax2.legend_.remove() # seaborn automatically creates a new legend
ax3 = ax1.twinx()
sns.barplot(x=x, y=Z, hue=[names[3]] * len(x), hue_order=names, palette=colors, alpha=0.7, ax=ax3)
ax3.legend_.remove()
ax3.spines['right'].set_position(('axes', 1.15))
ax1.set_ylabel("First", color=colors[0])
ax2.set_ylabel("Second", color=colors[2])
ax3.set_ylabel("Third", color=colors[3])
ax1.tick_params(axis='y', colors=colors[0])
ax2.tick_params(axis='y', colors=colors[2])
ax3.tick_params(axis='y', colors=colors[3])
ax2.spines['right'].set_color(colors[2])
ax3.spines['right'].set_color(colors[3])
plt.tight_layout()
plt.show()