PyDataset | Instant access to many datasets in Python | Dataset library
kandi X-RAY | PyDataset Summary
kandi X-RAY | PyDataset Summary
Provides instant access to many datasets right from Python (in pandas DataFrame structure).
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Top functions reviewed by kandi - BETA
- Return a pandas dataframe
- Setup the data repo
- Try to find similar words
- Return the path to the rdata folder
- Return all available datasets
- Convert an HTML entity name into a C ++ code
- Process data
- Simple CSS parser
- Escape a markdown section
- Find the most similar words
- Convert the character name to the C - code
- Write text to stdout
- Replace entities in s
- Get character reference
- Return entity reference
- Unescape a string
PyDataset Key Features
PyDataset Examples and Code Snippets
Lines of Code : 10License : Strong Copyleft (CC BY-SA 4.0)
Copysudo mkdir /usr/local/share/jupyter
sudo chmod 777 /usr/local/share/jupyter
jupyter nbextension install --py luxwidget
jupyter nbextension enable --py luxwidget
jupplt.title = "Population Graph"
def min_max(x):
return max(x)-min(x)
def perc(x):
return x.quantile(0.15)
mtcars.agg(['mean',min_max,perc])
mpg cyl disp hp drat wt qsec vs am gear carb
mean 2i = tab.columns.levels[0]
out = sorted(i.difference([mn]))
out.append(mn)
new = pd.CategoricalIndex(i, ordered=True, categories=out)
tab.columns = tab.columns.set_levels(new,level=0)
tab = tab.sort_index(axis=1, ascending=[True, False])
fig.layout.legend.y = 1.05
fig.layout.legend.x = 1.035
fig.layout.coloraxis.colorbar.y = 0.35
from pydataset import data
import plotly.express as px
mtcars = data('mtcars')
mtcars.am = mtcars.am.astype('category')
import altair as alt
from pydataset import data
df = data('sleepstudy')
alt.Chart(df).transform_joinaggregate(
maxReaction='max(Reaction)',
groupby=['Subject']
).mark_line().encode(
x=alt.X('Days:O', title=''),
y=alt.Y('Rplt.savefig('test.png', bbox_inches="tight")
fig.savefig('test.png', bbox_inches="tight")
df.groupby('Sepal.Length', as_index=True).apply(lambda x: x if len(x)>1 else None)
ndf = df.drop(df.drop_duplicates(subset='Sepal.Length', keep=False).index)
# keep first duplicates
d1=data = pd.read_csv('iris.data.txt', sep=',', header=None)
data.columns = ['Sepal.Length' , 'Sepal.Width' , 'Petal.Length', 'Petal.Width' ,'Species' , 'ID']
data['ID'] = data.index
#I guess you dont want these
data.drop(['Petal.Width','Pepd.concat([df1.reset_index(),df2.reset_index()],ignore_index=True)
categories counts freqs
0 automatic 13 0.40625
1 manual 19 0.59375
2 Straight Engine 18 0.56250
3 Community Discussions
Trending Discussions on PyDataset
QUESTION
I'm having trouble running the Lux library on my Notebook.
I've tried following the instructions on their README file and looked for answers on Stack, nothing.
Here are my inputs and outputs:
Input 1:
...ANSWER
Answered 2021-Nov-16 at 11:25It seems that lux relies on the /usr/local/share/jupyter folder.
My solution was to create a new folder with
QUESTION
Actually I want to give title to my line plot of matplotlib.pyplot line plot, but I am facing this error
"TypeError: 'str' object is not callable while giving title to the matplotlib.pyplot of line line plot"
Here is my code.
` import numpy as np import pandas as pd from matplotlib import pyplot as plt from pydataset import data
austres = data('austres') austres.head()
plt.figure(figsize=(10,4)) # plot_size
plt.plot(austres['time'], austres['austres'], 'v-g')
plt.title(label="Population Graph")enter code here
plt.xlabel('Time')
plt.ylabel('Population')
`
ANSWER
Answered 2021-Sep-30 at 08:37Probable reason is you assigned to plt.title before. Someting like
QUESTION
Request help on why the following is giving error?:
...ANSWER
Answered 2021-Jul-26 at 19:59Reading the answer by @James my guess is that you need to write the custom function such that the function is applied on the series and not over each element. Maybe someone else who is more familiar with the underlying pandas code can chip in:
QUESTION
This is a side-problem caused by an answer form another question.
I do combine two crosstab() results with counted and normalized values. The problem is that the resulting column names are not in the right order. "Right" means that the margins_name (in my example it is "gesamt") should always appear at the last row/column and not like this:
ANSWER
Answered 2021-Jul-14 at 09:36I would just select the total columns using a list comprehension and piece together the columns selection as desired:
QUESTION
Like ggplot2, can we have separate legends for Color, Symbol, etc. for a Plotly Express visualization?
...ANSWER
Answered 2021-Apr-20 at 18:58I think your latest attempt looks pretty good. And personally I don't see the need for the size of legend elements to reflect sizes in the figure itself as long as the details otherwise are clear. Here's a little setup to adjust your legend and colorbar:
QUESTION
I use Pandas and Dask all the time. I also have a number of custom classes and functions which I utilize a lot for different analyses, which I am always having to edit to account for either Dask or Pandas. I consistently find myself in a situation where I wish I could assign attributes to the dataset which I am analyzing, minimizing the compute command from dask and also allowing easier management of functions as I switch between data types. Something effectively akin to:
ANSWER
Answered 2020-Dec-05 at 22:45In the upcoming release of Dask, you will be able to do this by using the recent attrs feature in pandas 1.0. For now, you can pip install dask from Github to use this functionality.
QUESTION
I am attempting to apply the gower_matrix function from the gower package to the values of a dictionary using this chunk of code:
ANSWER
Answered 2020-Sep-02 at 16:37Based on a web search for ufunc 'true_divide' output, it appears that the error occurs (not a Numpy bug, but behaviour that changed several years ago) when attempting to divide an array of integer values through by a floating-point value. It appears to be an unspecified requirement of the gower package that you pass in floating-point values. So convert the cars data first. My guess is that you have some columns that contain floating-point values and some that contain integers; the test element of combo_dicts works fine because it happens to have been produced only from floating-point columns.
QUESTION
I want to install pydataset package in anaconda, below pip command installs it on python 2.7, but I have python 3.7 for Jupyter notebook. How to install pydataset using conda command?
...ANSWER
Answered 2020-May-08 at 21:15You can issue that same command inside of an anaconda prompt.
See here:
Occasionally a package is needed which is not available as a conda package but is available on PyPI and can be installed with pip. In these cases, it makes sense to try to use both conda and pip.
QUESTION
I am trying to create a facet plot to compare the reaction times of subjects from a sleep deprivation study. The data come from the sleepstudy dataset, available in the pydataset package.
By using altair.condition I am able to style the lines differently. The problem is that I am not getting the result I would like to obtain. I aim to highlight in orange only the lines that exceeds 400 (ms) at least once, namely the subjects 308, 332, and 337 in the chart below.
The alt.condition I am using in the code below seems to test only the first datum of the df.Reaction Pandas Series.
I am using altair 4.0.1.
ANSWER
Answered 2020-Jan-28 at 20:58You can do this by using a joinaggregate transform to compute the maximum value within each pane, and then color based on this maximum:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install PyDataset
You can use PyDataset like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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