Jupyter数据科学分析环境-R python Julia
为方便快速习惯环境和快速入门,可以通过以下的网址和用户名和密码进行学习和测试。
网址:ssh登陆 jupyterhub:http://xyz.weinformatics.com:30016/hub/login?next=%2Fhub%2F
你也可以登陆以下网址10s快速注册获取
用户名和密码如下:注请大家随机选择,我们推荐用户使用ssh登陆或者申请自己的账号做分析
恒诺新知用户名:mynewuser2 密码:1234506
恒诺新知用户名:mynewuser3 密码:1523456
恒诺新知用户名:mynewuser4 密码:123456
恒诺新知用户名:mynewuser5 密码:123456
恒诺新知用户名:mynewuser6 密码:1253456
我们推荐使用该环境进行python的学习,以下安装seaborn进行绘图
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple seaborn
Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple
Collecting seaborn
Downloading https://pypi.tuna.tsinghua.edu.cn/packages/e7/f9/f0b53f88060247251bf481fa6ea62cd0d25bf1b11a87888e53ce5b7c8ad2/pytz-2019.3-py2.py3-none-any.whl (509 kB)
|████████████████████████████████| 509 kB 45.8 MB/s eta 0:00:01
Collecting cycler>=0.10
Downloading https://pypi.tuna.tsinghua.edu.cn/packages/f7/d2/e07d3ebb2bd7af696440ce7e754c59dd546ffe1bbe732c8ab68b9c834e61/cycler-0.10.0-py2.py3-none-any.whl (6.5 kB)
Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.8/dist-packages (from matplotlib>=2.1.2->seaborn) (2.4.6)
Collecting kiwisolver>=1.0.1
Downloading https://pypi.tuna.tsinghua.edu.cn/packages/36/ac/c8627c214954b18b197f137ee96bc99e1cc31913d80d7ad59fbab3b05945/kiwisolver-1.2.0-cp38-cp38-manylinux1_x86_64.whl (92 kB)
|████████████████████████████████| 92 kB 167 kB/s eta 0:00:01
Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.8/dist-packages (from python-dateutil>=2.6.1->pandas>=0.22.0->seaborn) (1.14.0)
Installing collected packages: numpy, pytz, pandas, scipy, cycler, kiwisolver, matplotlib, seaborn
WARNING: The scripts f2py, f2py3 and f2py3.8 are installed in '/home/mynewuser1/.local/bin' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
Successfully installed cycler-0.10.0 kiwisolver-1.2.0 matplotlib-3.2.1 numpy-1.18.2 pandas-1.0.3 pytz-2019.3 scipy-1.4.1 seaborn-0.10.0
Note: you may need to restart the kernel to use updated packages.
安装完成后,提示我们需要重启内核

然后就可以根据官方教程进行学习:http://seaborn.pydata.org/index.html
import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="whitegrid")
# Load the example diamonds dataset
diamonds = sns.load_dataset("diamonds")
# Draw a scatter plot while assigning point colors and sizes to different
# variables in the dataset
f, ax = plt.subplots(figsize=(6.5, 6.5))
sns.despine(f, left=True, bottom=True)
clarity_ranking = ["I1", "SI2", "SI1", "VS2", "VS1", "VVS2", "VVS1", "IF"]
sns.scatterplot(x="carat", y="price",
hue="clarity", size="depth",
palette="ch:r=-.2,d=.3_r",
hue_order=clarity_ranking,
sizes=(1, 8), linewidth=0,
data=diamonds, ax=ax)

python的扩展包是python的十倍,从网上总能找到解决你的问题满足你需求的。
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