熊猫describe（）未显示

我正在学习有关机器学习的Google课程，并试图使其在Atom上运行，而不是简单地使用colab版本。模型训练和其他工作进展顺利，但使用describe（）函数时遇到问题。我已经查阅了文档，但是仍然无法显示摘要。它仅在我在命令行上尝试交互式python时有效。我的代码的相关部分如下。谢谢您的帮助。

import math

from IPython import display
from matplotlib import cm
from matplotlib import gridspec
from matplotlib import pyplot as plt
import numpy as np
import pandas as pd
from sklearn import metrics
import tensorflow as tf
from tensorflow.python.data import Dataset

tf.logging.set_verbosity(tf.logging.ERROR)
pd.options.display.max_rows = 10
pd.options.display.float_format = '{:.lf}'.format

# Load data set
california_housing_dataframe = pd.read_csv("https://storage.googleapis.com/mledu-datasets/california_housing_train.csv", sep=",")

......

# Split the data set into training sets of the first 12000/17000 examples,
training_examples = preprocess_features(california_housing_dataframe.head(12000))
training_targets = preprocess_targets(california_housing_dataframe.head(12000))

# and validation sets of the last 5000/17000 examples.
validation_examples = preprocess_features(california_housing_dataframe.tail(5000))
validation_targets = preprocess_targets(california_housing_dataframe.tail(5000))

# Double-check that the splitting is correct. (NOT WORKING YET)
print("Training examples summary:")
training_examples.describe()

Training examples summary: 
Validation examples summary: 
Training targets summary: 
Validation targets summary: