Seaborn load_dataset
Question:
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_dataset("tips")
is not explained at all. I have located the tips.csv file, but I can’t seem to find adequate documentation on what load_dataset specifically does. I tried to create my own csv and load this, but to no avail. I also renamed the tips file and it still worked…
My question is thus:
Where is load_dataset actually looking for files? Can I actually use this for my own boxplots?
EDIT: I managed to get my own boxplots working using my own DataFrame, but I am still wondering whether load_dataset is used for anything more than mysterious tutorial examples.
Answers:
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')
Just to add to ‘selwyth’s’ answer.
import pandas as pd
Data=pd.read_csv('Pathtocsv')
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.
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!
You will need to have an internet connection since the csv files are not on your local computer so your computer needs to be online in order to download the dataset
load_dataset is used for seaborn datasets;if you want to use your own dataset, you should open(or read )it with Pandas and after it you can use seaborn methods to Draw diagrams and visualization tasks. for example in Jupyter Notebook I’ve put my own dataset in my local drive and a document in my machine and read it :
import pandas as pd
import seaborn as sns
AI_df=pd.read_csv('AI.csv')
ai_cor=AI_df.corr()
sns.heatmap(ai_cor,annot=True,cmap='coolwarm',linewidths=1)
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_dataset("tips")
is not explained at all. I have located the tips.csv file, but I can’t seem to find adequate documentation on what load_dataset specifically does. I tried to create my own csv and load this, but to no avail. I also renamed the tips file and it still worked…
My question is thus:
Where is load_dataset actually looking for files? Can I actually use this for my own boxplots?
EDIT: I managed to get my own boxplots working using my own DataFrame, but I am still wondering whether load_dataset is used for anything more than mysterious tutorial examples.
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_nameskws : 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')
Just to add to ‘selwyth’s’ answer.
import pandas as pd
Data=pd.read_csv('Pathtocsv')
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.
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!
You will need to have an internet connection since the csv files are not on your local computer so your computer needs to be online in order to download the dataset
load_dataset is used for seaborn datasets;if you want to use your own dataset, you should open(or read )it with Pandas and after it you can use seaborn methods to Draw diagrams and visualization tasks. for example in Jupyter Notebook I’ve put my own dataset in my local drive and a document in my machine and read it :
import pandas as pd
import seaborn as sns
AI_df=pd.read_csv('AI.csv')
ai_cor=AI_df.corr()
sns.heatmap(ai_cor,annot=True,cmap='coolwarm',linewidths=1)