I am trying to get a grouped boxplot working using Seaborn as per the example
I can get the above example working, however the line:
tips = sns.load_
Just to add to 'selwyth's' answer.
import pandas as pd
Data=pd.read_csv('Path\to\csv\')
Data.head(10)
Once you have completed these steps successfully. Now the plotting actually works like this.
Let's say you want to plot a bar plot.
sns.barplot(x=Data.Year,y=Data.Salary) //year and salary attributes were present in my dataset.
This actually works with every plotting in seaborn.
Moreover, we will not be eligible to add our own dataset on Seaborn Git.
load_dataset
looks for online csv files on https://github.com/mwaskom/seaborn-data. Here's the docstring:
Load a dataset from the online repository (requires internet).
Parameters
name : str Name of the dataset (
name
.csv on https://github.com/mwaskom/seaborn-data). You can obtain list of available datasets using :func:get_dataset_names
kws : dict, optional Passed to pandas.read_csv
If you want to modify that online dataset or bring in your own data, you likely have to use pandas. load_dataset
actually returns a pandas DataFrame
object, which you can confirm with type(tips)
.
If you already created your own data in a csv file called, say, tips2.csv, and saved it in the same location as your script, use this (after installing pandas) to load it in:
import pandas as pd
tips2 = pd.read_csv('tips2.csv')
Download all csv files(zipped) to be used for your example from here.
Extract the zip file to a local directory and launch your jupyter notebook from the same directory. Run the following commands in jupyter notebook:
import pandas as pd
tips = pd.read_csv('seaborn-data-master/tips.csv')
you're good to work with your example now!