我有一个数据集,其中包含一个类别字段,“城市”和2个指标,年龄和权重。我想使用循环为每个城市绘制一个散点图。但是我正努力在单个语句中将我需要的group by循环组合起来。如果我只使用for循环,我最终会得到每个记录的图表,如果我按照我的方式进行分组,我会得到正确数量的图表但没有值。
这是我的代码,只使用了我的组的for循环,注释掉了:
import pandas as pd
import numpy as np
import matplotlib.pylab as plt
d = { 'City': pd.Series(['London','New York', 'New York', 'London', 'Paris',
'Paris','New York', 'New York', 'London','Paris']),
'Age' : pd.Series([36., 42., 6., 66., 38.,18.,22.,43.,34.,54]),
'Weight': pd.Series([225,454,345,355,234,198,400, 256,323,310])
}
df = pd.DataFrame(d)
#for C in df.groupby('City'):
for C in df.City:
fig = plt.figure(figsize=(5, 4))
# Create an Axes object.
ax = fig.add_subplot(1,1,1) # one row, one column, first plot
# Plot the data.
ax.scatter(df.Age,df.Weight, df.City == C, color="red", marker="^")
答案 0 :(得分:2)
不要多次拨打plt.figure
,因为每次通话都会创建一个新的数字(粗略地讲,窗口)。
import pandas as pd
import numpy as np
import matplotlib.pylab as plt
d = {'City': ['London', 'New York', 'New York', 'London', 'Paris',
'Paris', 'New York', 'New York', 'London', 'Paris'],
'Age': [36., 42., 6., 66., 38., 18., 22., 43., 34., 54],
'Weight': [225, 454, 345, 355, 234, 198, 400, 256, 323, 310]}
df = pd.DataFrame(d)
fig, ax = plt.subplots(figsize=(5, 4)) # 1
df.groupby(['City']).plot(kind='scatter', x='Age', y='Weight',
ax=ax, # 2
color=['red', 'blue', 'green'])
plt.show()
plt.subplots
返回一个数字fig
和一个轴ax
。ax=ax
传递给Panda的情节方法,那么所有的情节都会如此
如何在同一轴上。为每个城市制作一个单独的数字:
import pandas as pd
import numpy as np
import matplotlib.pylab as plt
d = {'City': ['London', 'New York', 'New York', 'London', 'Paris',
'Paris', 'New York', 'New York', 'London', 'Paris'],
'Age': [36., 42., 6., 66., 38., 18., 22., 43., 34., 54],
'Weight': [225, 454, 345, 355, 234, 198, 400, 256, 323, 310]}
df = pd.DataFrame(d)
groups = df.groupby(['City'])
for city, grp in groups: # 1
fig, ax = plt.subplots(figsize=(5, 4))
grp.plot(kind='scatter', x='Age', y='Weight', # 2
ax=ax)
plt.show()
grp
,子数据框而不是df
。答案 1 :(得分:2)
我在另一篇文章中使用了group by并插入到我的代码中,为每个组生成一个图表:
import pandas as pd
import numpy as np
import matplotlib.pylab as plt
d = { 'City': pd.Series(['London','New York', 'New York', 'London','Paris',
'Paris','New York', 'New York', 'London','Paris']),
'Age' : pd.Series([36., 42., 6., 66., 38.,18.,22.,43.,34.,54]) ,
'Weight': pd.Series([225,454,345,355,234,198,400, 256,323,310])
}
df = pd.DataFrame(d)
groups = df.groupby(['City'])
for city, grp in groups:
fig = plt.figure(figsize=(5, 4))
# Create an Axes object.
ax = fig.add_subplot(1,1,1) # one row, one column, first plot
# Plot the data.
ax.scatter(df.Age,df.Weight, df.City == city, color="red", marker="^")