如何修复:TypeError:没有要绘制的数字数据
在本文中,我们将修复错误:TypeError: no numeric data to plot
出现此错误的案例:
Python3
# importing pandas
import pandas as pd
# importing numpy
import numpy as np
import matplotlib.pyplot as plt
petal_length = ['3.3', '3.5', '4.0', '4.5',
'4.6', '5.0', '5.5', '6.0',
'6.5', '7.0']
petal_width = ['3.6', '3.8', '4.4', '6.6',
'6.8', '7.0', '7.5', '8.0',
'8.5', '8.9']
df = pd.DataFrame({'petal_length(cm)': petal_length,
'petal_width(cm)': petal_width})
df.plot(x='petal_length(cm)', y='petal_width(cm)')
plt.show()
Python3
# importing pandas
import pandas as pd
# importing numpy
import numpy as np
# importing matplotlib.pyplot
import matplotlib.pyplot as plt
petal_length = ['3.3', '3.5', '4.0', '4.5',
'4.6', '5.0', '5.5', '6.0',
'6.5', '7.0']
petal_width = ['3.6', '3.8', '4.4', '6.6',
'6.8', '7.0', '7.5', '8.0',
'8.5', '8.9']
df = pd.DataFrame({'petal_length(cm)': petal_length,
'petal_width(cm)': petal_width})
df['petal_length(cm)'] = df['petal_length(cm)'].astype(float)
df['petal_width(cm)'] = df['petal_width(cm)'].astype(float)
df.plot(x='petal_length(cm)', y='petal_width(cm)')
plt.show()
Python3
# importing pandas
import pandas as pd
# importing numpy
import numpy as np
# importing matplotlib.pyplot
import matplotlib.pyplot as plt
petal_length = ['3.3', '3.5', '4.0', '4.5',
'4.6', '5.0', '5.5', '6.0',
'6.5', '7.0']
petal_width = ['3.6', '3.8', '4.4', '6.6',
'6.8', '7.0', '7.5', '8.0',
'8.5', '8.9']
df = pd.DataFrame({'petal_length(cm)': petal_length,
'petal_width(cm)': petal_width})
# Using to_numeric() function
df['petal_length(cm)'] = pd.to_numeric(df['petal_length(cm)'])
df['petal_width(cm)'] = pd.to_numeric(df['petal_width(cm)'])
df.plot(x='petal_length(cm)', y='petal_width(cm)')
plt.show()
输出:
TypeError: no numeric data to plot
错误原因:
当我们绘制数据类型与此错误引发的数值数据不同的数据时,只能对数值数据进行绘图。要知道数据类型是否为数字,我们可以使用函数dtypes() 知道它。
print(df.dtypes)
我们用来绘制的数据必须是数字的。
修复错误:
可以通过将要绘制的数据转换为数值数据来修复此错误。要将数据转换为数字数据,我们可以使用函数 astype() 或 to_numeric()。
方法一:使用astype()函数
句法:
df['column_name']= df['column_name'].astype(data_type)
其中,df 是输入数据帧
例子:
Python3
# importing pandas
import pandas as pd
# importing numpy
import numpy as np
# importing matplotlib.pyplot
import matplotlib.pyplot as plt
petal_length = ['3.3', '3.5', '4.0', '4.5',
'4.6', '5.0', '5.5', '6.0',
'6.5', '7.0']
petal_width = ['3.6', '3.8', '4.4', '6.6',
'6.8', '7.0', '7.5', '8.0',
'8.5', '8.9']
df = pd.DataFrame({'petal_length(cm)': petal_length,
'petal_width(cm)': petal_width})
df['petal_length(cm)'] = df['petal_length(cm)'].astype(float)
df['petal_width(cm)'] = df['petal_width(cm)'].astype(float)
df.plot(x='petal_length(cm)', y='petal_width(cm)')
plt.show()
输出:
方法二:使用to_numeric()函数
句法:
df['column_name'] = pd.to_numeric(df['column_name'])
其中 df 是输入数据帧
示例:
Python3
# importing pandas
import pandas as pd
# importing numpy
import numpy as np
# importing matplotlib.pyplot
import matplotlib.pyplot as plt
petal_length = ['3.3', '3.5', '4.0', '4.5',
'4.6', '5.0', '5.5', '6.0',
'6.5', '7.0']
petal_width = ['3.6', '3.8', '4.4', '6.6',
'6.8', '7.0', '7.5', '8.0',
'8.5', '8.9']
df = pd.DataFrame({'petal_length(cm)': petal_length,
'petal_width(cm)': petal_width})
# Using to_numeric() function
df['petal_length(cm)'] = pd.to_numeric(df['petal_length(cm)'])
df['petal_width(cm)'] = pd.to_numeric(df['petal_width(cm)'])
df.plot(x='petal_length(cm)', y='petal_width(cm)')
plt.show()
输出: