在绘制绘图时,我使用了Jupyter Notebook和Pycharm,并使用了相同的代码和包。代码是:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt # as in Pycharm
import matplotlib as plt # as in Jupyter
df = pd.read_csv("/home/kunal/Downloads/Loan_Prediction/train.csv")
df['ApplicantIncome'].
有没有办法使用cmake find_package()来定位jupyter_notebook安装? 我试过了 FIND_PACKAGE(jupyter-notebook REQUIRED) 但是它错误地输出了 CMake Error at CMakeLists.txt:15 (FIND_PACKAGE):
By not providing "Findjupyter-notebook.cmake" in CMAKE_MODULE_PATH this
project has asked CMake to find a package configuration file
运行jupyter notebook和jupyter server给出了非常相似的结果,而且描述也非常相似。
❯ jupyter notebook -h
The Jupyter HTML Notebook.
This launches a Tornado based HTML Notebook Server that serves up an
HTML5/Javascript Notebook client.
❯ jupyter server -h
The Jupyter Server.
This launches a Tornado-based Jupyter Server.
有一些不
我使用这里的链接中的步骤设置了数据流程
但是我的电脑一直要密码
我没有设置任何密码。
我试过我的google账号密码,但是密码不起作用
我运行了../root$ sudo grep -ir password并获得了以下结果,因此确认没有设置密码
.jupyter/jupyter_notebook_config.py:## Hashed password to use for web authentication.
.jupyter/jupyter_notebook_config.py:# The string should be of the form type:salt:has
当我尝试运行命令jupyter-notebook时,会得到以下错误:
`Traceback (most recent call last):
File "/home/leo/anaconda2/bin/jupyter-notebook", line 7, in <module>
from notebook.notebookapp import main
File "/usr/lib/python3/dist-packages/notebook/notebookapp.py", line 31, in <module>
我是数据科学和Python编程的新手。在jupyter笔记本中加载csv文件时遇到问题。
这是针对Windows10的,我已经尝试过重启内核并清除输出。
import numpy as np
import pandas as pd
data = pd.read_csv("C/users/SHIVAM/desktop/brazil.csv.csv")
我希望数据集加载到jupyter notebook中。它还会引发找不到文件的错误。
当我尝试使用以下代码导入.txt文件时,收到以下错误消息:
with open("cobuy.txt", "r+") as my_file:
for item in my_file:
my_file.write("%s\n" % item)
text = open("obuy.txt").read()
text
IOPub data rate exceeded.
The notebook server will temporarily stop sending output
to the client
我使用for循环来合并jupyter notebook上的csv文件,但是我的结果返回了一个列表,而不是一个数据帧。谁能帮帮我,告诉我哪里做错了?提前谢谢你。
files = ['babd_light_z1.csv','babd_light_z2.csv','babd_light_z3.csv']
data = []
for f in files:
data.append(pd.read_csv(f))
type(data) # returns list