import pandas as pd from pyecharts import options as opts from pyecharts.charts import Boxplot, Line, Grid # 读取数据 df = pd.read_excel('200马力拖拉机明细.xlsx') # 创建DataFrame df = pd.DataFrame({ 'FactoryName': df['FactoryName'], 'JiJXH': df['JiJXH'], 'sale': df['sale'] }) # 将FactoryName和JiJXH合并为一列 df['FactoryName-JiJXH'] = df['FactoryName'] + '-' + df['JiJXH'].astype(str) # 对FactoryName-JiJXH进行分组 grouped = df.groupby('FactoryName-JiJXH') # 绘制箱线图 box = Boxplot() box_data = [] for name, group in grouped: box_data.append([round(i, 2) for i in group['sale'].tolist()]) box.add_xaxis([name]) box.add_yaxis('', box.prepare_data(box_data), tooltip_opts=opts.TooltipOpts(trigger='axis', axis_pointer_type='cross')) box.set_global_opts( title_opts=opts.TitleOpts(title='Sale Boxplot', subtitle=''), xaxis_opts=opts.AxisOpts( axislabel_opts=opts.LabelOpts(interval=0, formatter='{value|换行}'.replace('换行', '\n')) ) ) box.set_series_opts(label_opts=opts.LabelOpts(is_show=False)) # 绘制折线图 line = Line() for name, group in grouped: line.add_xaxis([name]) line.add_yaxis('Median', [round(group['sale'].median(), 2)], label_opts=opts.LabelOpts(is_show=False)) line.set_global_opts( title_opts=opts.TitleOpts(title='Sale Median Line', subtitle=''), xaxis_opts=opts.AxisOpts( axislabel_opts=opts.LabelOpts(interval=0, formatter='{value|换行}'.replace('换行', '\n')) ) ) # 合并图表 grid = Grid( init_opts=opts.InitOpts( width='1400px', height='800px', page_title='Boxplot and Median Line', theme='white' ) ) grid.add(box, grid_opts=opts.GridOpts(pos_left='10%', pos_right='10%')) grid.add(line, grid_opts=opts.GridOpts(pos_left='10%', pos_right='10%')) grid.render('boxplot_and_line.html') 提示list index out of range

这个错误通常是由于没有找到所需的列名或行数不够导致的。请确保以下两点：

1. 文件路径正确，确保文件可以正确读取

2. DataFrame 中包含所需的列名

您可以通过在代码中添加一些 `print` 语句来进行调试，以找出问题所在。例如，在 `df` 的创建后，您可以添加下面这行代码来查看 DataFrame 中是否包含所需的列名：

print(df.columns)

或者您可以在读取 excel 文件之后添加下面这行代码来查看 DataFrame 的行数：

print(df.shape[0])

希望这可以帮助您找出问题所在。

相关问题

import pandas as pd from pyecharts.charts import Boxplot # 读取csv文件 data = pd.read_csv('kag_risk_factors_cervical_cancer(1).csv') # 去掉空值 data = data.dropna() # 构造数据 values = [] for column_name in data.columns[2:]: values.append(list(data[column_name])) # 绘制箱型图 boxplot = ( Boxplot() .add_xaxis(list(data.columns[2:])) .add_yaxis("", box_data=values) .set_global_opts(title_opts=opts.TitleOpts(title="Risk Factors of Cervical Cancer")) ) # 显示图表 boxplot.render_notebook() TypeError: add_yaxis() got an unexpected keyword argument 'data_pair'怎么解决

这个错误是因为 pyecharts 最新版本更新了 add_yaxis() 函数，将原来的 data_pair 参数改为了 box_data。你需要将代码中的 data_pair 改为 box_data，如下所示：

import pandas as pd
from pyecharts.charts import Boxplot

# 读取csv文件
data = pd.read_csv('kag_risk_factors_cervical_cancer(1).csv')

# 去掉空值
data = data.dropna()

# 构造数据
values = []
for column_name in data.columns[2:]:
    values.append(list(data[column_name]))

# 绘制箱型图
boxplot = (
    Boxplot()
    .add_xaxis(list(data.columns[2:]))
    .add_yaxis("", box_data=values)  # 将 data_pair 改为 box_data
    .set_global_opts(title_opts=opts.TitleOpts(title="Risk Factors of Cervical Cancer"))
)

# 显示图表
boxplot.render_notebook()

这样就可以成功绘制箱型图了。

age_preg_bar = px.box(risk_factor_df, x="age_cat", y="Num of pregnancies", color_discrete_sequence=["darkblue"], points="outliers", category_orders=["Teenager", "Twenties", "Thirties", "Forties", "Fifties", "Seventy and over"]) age_preg_bar.update_xaxes(title="Age Category") age_preg_bar.update_yaxes(title="Number of Pregnancies") age_preg_bar.update_layout(title="Distribution of number of pregnancies per age group") age_preg_bar.show()用pyecharts绘制代码

以下是使用pyecharts绘制类似的箱线图的代码：

from pyecharts.charts import Boxplot
from pyecharts import options as opts
import pandas as pd

# 读入数据
risk_factor_df = pd.read_csv('risk_factor.csv')

# 按照年龄分组
groups = risk_factor_df.groupby('age_cat')['Num of pregnancies'].apply(list).reset_index()

# 绘制箱线图
boxplot = Boxplot().add_xaxis(groups['age_cat'].tolist()) \
    .add_yaxis("", box_data=groups['Num of pregnancies'].tolist(), \
               color="#5470c6", \
               itemstyle_opts=opts.ItemStyleOpts(border_color="#5470c6",
                                                 border_width=2,
                                                 border_type="solid")) \
    .set_global_opts(title_opts=opts.TitleOpts(title="Distribution of number of pregnancies per age group"),
                     yaxis_opts=opts.AxisOpts(name="Number of Pregnancies"),
                     xaxis_opts=opts.AxisOpts(name="Age Category"))

boxplot.render_notebook()

需要注意的是，pyecharts中的Boxplot图并没有针对离群点(points="outliers")进行单独的处理，而是将所有数据都绘制在同一个图中。如果需要将离群点单独绘制，可以考虑使用其他的图表类型或者自己对数据进行处理再绘图。