KeyError: (u' 192.168.32.6 ',)

This error message suggests that there is a KeyError in a Python program, indicating that the key (u' 192.168.32.6 ',) is not found in a dictionary or other data structure. The key may be misspelled, or it may not exist in the data structure being accessed. It is also possible that the data structure has been modified in some way that causes the key to no longer be present. To resolve this issue, the program will need to be debugged to identify the specific location where the KeyError is occurring and then appropriate modifications will need to be made to the program to fix the issue.

相关问题

tooltip: { trigger: 'axis', axisPointer: { type: 'cross' } }, grid: { right: '20%' }, toolbox: { feature: { dataView: { show: true, readOnly: false }, restore: { show: true }, saveAsImage: { show: true } } }, legend: { data: ['Evaporation', 'Precipitation', 'Temperature'] }, xAxis: [ { type: 'category', axisTick: { alignWithLabel: true }, // prettier-ignore data: ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'] } ], yAxis: [ { type: 'value', name: 'Evaporation', position: 'right', alignTicks: true, axisLine: { show: true, lineStyle: { color: colors[0] } }, axisLabel: { formatter: '{value} ml' } }, { type: 'value', name: 'Precipitation', position: 'right', alignTicks: true, offset: 80, axisLine: { show: true, lineStyle: { color: colors[1] } }, axisLabel: { formatter: '{value} ml' } }, { type: 'value', name: '温度', position: 'left', alignTicks: true, axisLine: { show: true, lineStyle: { color: colors[2] } }, axisLabel: { formatter: '{value} °C' } } ], series: [ { name: 'Evaporation', type: 'bar', data: [ 2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3 ] }, { name: 'Precipitation', type: 'bar', yAxisIndex: 1, data: [ 2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3 ] }, { name: 'Temperature', type: 'line', yAxisIndex: 2, data: [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2] } ]详细解释这段代码

这段代码是一个基于 echarts 的图表配置，用于展示三种不同数据在不同时间段内的变化情况，分别是蒸发量、降水量和温度。以下是每个配置项的详细解释：

1. tooltip：鼠标悬停在图表上时显示的提示框配置，这里是触发方式为 axis，即在坐标轴上触发，并且指针类型为 cross。

2. grid：图表的网格配置，这里将右边的空间占据了 20%。

3. toolbox：图表工具箱的配置，包括数据视图、恢复、保存为图片等。

4. legend：图例的配置，即每个数据系列的名称。

5. xAxis：X 轴的配置，这里是一个类目轴，即每个刻度代表一个类别，如月份。

6. yAxis：Y 轴的配置，这里有三个 Y 轴，分别对应蒸发量、降水量和温度，其中第二个 Y 轴偏移了 80px。

7. series：数据系列的配置，这里有三个数据系列，分别是蒸发量、降水量和温度。蒸发量和降水量使用的是柱状图，温度使用的是折线图，每个数据系列都有对应的名称、类型和数据。注意，第二个数据系列使用了第二个 Y 轴。

import numpy as np import matplotlib.pyplot as plt plt.rcParams[‘font.sans-serif’]=[‘SimHei’] plt.rcParams[‘axes.unicode_minus’]=False month_x=np.arange(1,13,1) data_tem=np.array([2.0,2.2,3.3,4.5,6.3,10.2,20.3,33.4,23.0,16.5,12.0,6.2]) data_precipitation=np.array([2.6,5.9,9.0,26.4,28.7,70.7,175.6,182.2,48.7,18.8,6.0,2.3]) data_evaporation=np.array([2.0,4.9,7.0,23.2,25.6,76.7,135.6,162.2,32.6,20.0,6.4,3.3]) fig,ax=plt.subplots() bar_ev=ax.bar(month_x,data_precipitation, color=‘pink’) bar_pre=ax.bar(month_x,data_precipitation, bottom=data_evaporation,color=‘skyblue’) ax.set_ylabel(‘水量(ml)’) ax.set_title(‘2020080603051’) ax_right=ax.twinx() line=ax_right.plot(month_x,data_tem,‘o-m’) ax_right.set_ylabel(‘气温(∘ ^\circ ∘ C)’) plt.legend([bar_ev,bar_pre,line[0]],[‘蒸发量’,‘降水量’,‘平均气温’],shadow=True,fancybox=True) plt.show()修改这段代码至python可运行

import numpy as np
import matplotlib.pyplot as plt

plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

month_x = np.arange(1, 13, 1)
data_tem = np.array([2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 33.4, 23.0, 16.5, 12.0, 6.2])
data_precipitation = np.array([2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3])
data_evaporation = np.array([2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3])

fig, ax = plt.subplots()
bar_ev = ax.bar(month_x, data_precipitation, color='pink')
bar_pre = ax.bar(month_x, data_precipitation, bottom=data_evaporation, color='skyblue')

ax.set_ylabel('水量(ml)')
ax.set_title('2020080603051')

ax_right = ax.twinx()
line = ax_right.plot(month_x, data_tem, 'o-m')
ax_right.set_ylabel('气温(℃)')

plt.legend([bar_ev, bar_pre, line[0]],
['蒸发量', '降水量', '平均气温'], shadow=True, fancybox=True)

plt.show()