Python 3.7, Openpyxl 2.5.12, O.S. Windows 7.
I would like to get majorGridlines with dot style. Is it possible to get this with openpyxl?
I have checked openpyxl.drawing.line.LineProperties class and I have seen there is an option called prstDash = "dot". I have managed to get dash and dot styles with different series of a ScatterChart() like:
serie.graphicalProperties.line.dashStyle = "sysDot"
However, I am not able to give this property to majorGridLines. Is there any way of doing it?
The best thing to do is to create a sample file with the styling you need and compare it with one created or processed by openpyxl. openpyxl implements the OOXML pretty closely so it should be possible to work out how what you need.
Update : 2022
Openpyxl 3.0.10, Python 3.8.3
#required modules to import
import openpyxl
from openpyxl.chart.shapes import GraphicalProperties
from openpyxl.drawing.line import LineProperties
from openpyxl.chart.axis import ChartLines
#Add dash style to majorgridlines or minorgridlines
chart = ScatterChart()
chart.y_axis.majorGridlines=
ChartLines(spPr=GraphicalProperties(ln=LineProperties(prstDash
= 'dash'))))
Related
What is the proper way to import a script that contains a period, such as program_1.4.py, ideally using importlib?
(Now that the imp module is deprecated, this this answer no longer applies: How to reference python package when filename contains a period .)
After looking through the CPython quite a lot and coming back to some other solutions (especially Import arbitrary python source file. (Python 3.3+)), I realized that I needed to pass the full path to my module. Here is the cross-platform, call-location-independent solution:
"""
import os, sys # For running from Notepad++ shortcut, etc
import importlib.machinery
program_1_4 = importlib.machinery.SourceFileLoader('program_1.4', os.path.join(sys.path[0], 'program_1.4.py')).load_module()
print(program_1_4)
program_1_4.main()
"""
He guys, I am just a beginner in Python3. I have a question :
import openpyxl
from openpyxl.style import *
As you can see that I am importing the openpyxl module, but why I need to import the second one in order to style fonts and cells an on.
openpyxl is a package. It contains modules, such as style. You should import the package anyway (all package or individual items). You can either:
import openpyxl
from openpyxl.style import *
then use style items like item1, item2
or
from openpyxl import style
then use style items like style.item1, style.item2
You don't have to - you can just as easily do:
import openpyxl
openpyxl.styles.fonts()
Or:
from openpyxl import style
style.fonts()
It comes down to personal preference. Using * imports is generally frowned upon because there's a risk of polluting the namespace, but if you know this isn't going to happen, and you want to keep your lines of code shorter, it's acceptable.
You are importing openpyxl, which includes everything in openpyxl including openpyxl.style and everything inside that. But say you would like to use X function of openpyxl.style, then you would have to write:
openpyxl.style.X()
If you write the second line you can simpy write:
X()
Basically the second line imports all the contents of the namespace openpyxl.style into your current namespace, removing the hassle of having to write openpyxl.style. everytime. Although it is generally a good practice to not merge namespaces like this, and not use
from _________ import *
Rather you can write
import openpyxl.style as op
and then use the X function as :
op.X()
You can also omit the line
import openpyxl
if you are not using anything else from openpyxl other than that included in openpyxl.style
I am trying to set the theme for bokeh plots on jupyter lab.
To do so I am following the official docs, copying the exact code from https://docs.bokeh.org/en/latest/docs/reference/themes.html.
However, I get an error cannot import name 'built_in_themes'.
I assume the default themes location changed, but can't seem to find anything else besides the said page documenting bokeh.themes.
I assume the default themes location changed
No, it has only ever been in the same location since it was added in version 1.0. The explanation is almost certainly that the version you are using is older than that.
As bigreddot said, same location.
Check your Bokeh version:
$ python3.7
>>> import sys
>>> print(sys.version)
>>> import bokeh
>>> print(bokeh.__version__)
Or via jupyter notebook:
import numpy as np
from bokeh.io import output_notebook, show
from bokeh.plotting import figure
Following the example here provided, the output should look like this:
Maybe you are just working in an environment with an older version.
After exporting a .dot file using scikit-learn's handy export_graphviz function.
I am trying to render the dot file using Graphviz into a cell in my Jupyter Notebook:
import graphviz
from IPython.display import display
with open("tree_1.dot") as f:
dot_graph = f.read()
display(graphviz.Source(dot_graph))
However the out[ ] is just an empty cell.
I am using graphviz 0.5 (pip then conda installed), iPython 5.1, and Python 3.5
The dot file looks correct here are the first characters:
digraph Tree {\nnode [shape=box, style="filled", color=
iPython display seems to work for other objects including Matplotlib plots and Pandas dataframes.
I should note the example on Graphviz' site also doesn't work.
It's possible that since you posted this, changes were made so you might want to update your libraries if that's possible.
The versions of relevance here I used are:
Python 2.7.10
IPython 5.1.0
graphviz 0.7.1
If you have a well formed .dot file, you can display it to the jupyter out[.] cell by the following:
import graphviz
with open("tree_1.dot") as f:
dot_graph = f.read()
# remove the display(...)
graphviz.Source(dot_graph)
this solution allows you to insert DOT text directly (without saving it to file first)
# convert a DOT source into graph directly
import graphviz
from IPython.display import display
source= '''\
digraph sample {
A[label="AL"]
B[label="BL"]
C[label="CL"]
A->B
B->C
B->D
D->C
C->A
}
'''
print (source)
gvz=graphviz.Source(source)
# produce PDF
#gvz.view()
print (gvz.source)
display(gvz)
Try to use pydotplus.
import pydotplus
by (1.1) Importing the .dot from outside
pydot_graph = pydotplus.graph_from_dot_file("clf.dot")
or (1.2) Directly using the .export_graphviz output
dt = tree.DecisionTreeClassifier()
dt = clf.fit(x,y)
dt_graphviz = tree.export_graphviz(dt, out_file = None)
pydot_graph = pydotplus.graph_from_dot_data(dt_graphviz)
(2.) and than display the pyplot graph using
from IPython.display import Image
Image(pydot_graph.create_png())
try to reinstall graphviz
conda remove graphviz
conda install python-graphviz
graphviz.Source(dot_graph).view()
graphviz.Source(dot_graph).view()
I am new to python and have a simple problem. In a first step, I want to load some sample data I created in Stata. In a second step, I would like to describe the data in python - that is, I'd like a list of the imported variable names. So far I've done this:
from pandas.io.stata import StataReader
reader = StataReader('sample_data.dta')
data = reader.data()
dir()
I get the following error:
anaconda/lib/python3.5/site-packages/pandas/io/stata.py:1375: UserWarning: 'data' is deprecated, use 'read' instead
warnings.warn("'data' is deprecated, use 'read' instead")
What does it mean and how can I resolve the issue? And, is dir() the right way to get an understanding of what variables I have in the data?
Using pandas.io.stata.StataReader.data to read from a stata file has been deprecated in pandas 0.18.1 version and hence you are getting that warning.
Instead, you must use pandas.read_stata to read the file as shown:
df = pd.read_stata('sample_data.dta')
df.dtypes ## Return the dtypes in this object
Sometimes this did not work for me especially when the dataset is large. So the thing I propose here is 2 steps (Stata and Python)
In Stata write the following commands:
export excel Cevdet.xlsx, firstrow(variables)
and to copy the variable labels write the following
describe, replace
list
export excel using myfile.xlsx, replace first(var)
restore
this will generate for you two files Cevdet.xlsx and myfile.xlsx
Now you go to your jupyter notebook
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_excel('Cevdet.xlsx')
This will allow you to read both files into jupyter (python 3)
My advice is to save this data file (especially if it is big)
df.to_pickle('Cevdet')
The next time you open jupyter you can simply run
df=pd.read_pickle("Cevdet")