在做数据分析的时候,有时候我们需要数据集,很多课程需要用到Titanic 的数据集: 我本地文档里面没有这个数据集,就直接从mwaskom/seaborn-data下载。文件里面是包含有titanic的数据集,然后即可读取出来需要的数据集。 这个数据集,我是直接下载下来,因为是CSV文件,所以直接用pandas直接读取:pd.read_csv('.
Python数据分析库 - Pandas Foundations II (Study with Titanic Dataset) - Michelle小梦想家 353 1 54:29 App Python数据分析库 - Pandas Foundations III (Study with Titanic Dataset) - Michelle小梦想家 6542 21 17:58 App LeetCode in Python 1. Two Sum LeetCode - Michelle小梦想家 1536 -- 11:...
Let’s customize this plot by including `sex` column from the dataset. import seaborn as sns import matplotlib.pyplot as plt titanic = sns.load_dataset("titanic") # customize the bar plot sns.barplot(x="class", y="fare", hue="sex", ci=None, palette="muted", data=titanic) # add ...
Now, since we understand the intuition behind the most basic machine learning algorithms used for classification problems, we can apply our knowledge to predict the survival outcome for those on board the Titanic. Our dataset will be borrowed from the Kaggle data science competitions platform. import...
plt.title('Missing Values in Titanic Dataset') plt.xlabel('Features') plt.ylabel('Number of Missing Values') plt.show() 通过查看缺失值的数量和分布情况,我们发现Age、Cabin和Embarked字段存在缺失值。对于Age,我们可以考虑使用均值、中位数或基于其他特征(如性别和舱位等级)的插值来填充。对于Cabin,由于缺...
('Dataset/Titanic/gender_submission.csv')89#Divide attributes and labels10titanic_labels = titanic_train['Survived'].copy()11titanic = titanic_train.drop(['Survived'],axis=1)1213#Feature Selection14fromsklearn.baseimportBaseEstimator, TransformerMixin1516classDataFrameSelector(BaseEstimator, ...
第一部分：数据可视化 pyecharts 类型：可视化图表设计 GitHub Star ：5985 功能：简洁的 API 设计，...
In this tutorial, you saw how to use MySQL Connector/Python to integrate a MySQL database with your Python application. You also saw some unique features of a MySQL database that differentiate it from other SQL databases. Along the way, you learned some programming best practices that are wor...
The following examples download the Titanic Tutorial notebook output: https://www.kaggle.com/code/alexisbcook/titanic-tutorialimport kagglehub # Download the latest version. kagglehub.notebook_output_download('alexisbcook/titanic-tutorial') # Download a specific version of the notebook output. ...
titanic= sns.load_dataset("titanic") tips= sns.load_dataset("tips") iris= sns.load_dataset("iris") #在带状图中,散点图通常会重叠。这使得很难看到数据的完全分布 sns.stripplot(x="day", y="total_bill", data=tips) sns.plt.show() ...