train_df.head(10).style.hide(axis='columns',subset=['Route'])\ .background_gradient(subset=['Journey_day','Journey_month','Dep_hour','Dep_min','Arrival_hour','Arrival_min'],cmap='winter')\ .background_gradient(subset=['Duration'], cmap='autumn')\ .bar(subset=['Price'])这些代码有错误
时间: 2023-09-01 13:13:44 浏览: 49
是的,这些代码有错误。根据Python语法,一行代码应该以一个完整的语句结束,或者使用续行符号\将它分成多行。在这段代码中,第一行以反斜杠结尾,但是没有继续下一行,因此会导致语法错误。此外,还缺少引入必要的库。可能需要添加以下内容:
```
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
```
正确的代码应该像这样:
```
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
train_df.head(10).style.hide(axis='columns',subset=['Route'])\
.background_gradient(subset=['Journey_day','Journey_month','Dep_hour','Dep_min','Arrival_hour','Arrival_min'],cmap='winter')\
.background_gradient(subset=['Duration'], cmap='autumn')\
.bar(subset=['Price'])
```
相关问题
df_old.drop(i_list, axis=0)
这个问题也涉及到数据框的操作,是一个IT类问题。回答如下:`df_old.drop(i_list, axis=0)` 是用来删除数据框 `df_old` 中指定索引(行)的方法。其中,`i_list` 是要删除的索引列表,`axis=0` 表示删除行。执行该方法后,将会返回删除后的新数据框,原数据框 `df_old` 不会被修改。
X_mean = X_train.mean(axis=0)
This line of code calculates the mean of the columns in the X_train dataset.
The "mean" function in numpy calculates the average of the specified axis. In this case, "axis=0" means that the function will calculate the mean of each column in the X_train dataset.
The resulting X_mean variable will be a numpy array containing the mean values for each column in X_train.