gallery/tryjesus_bl_nobg

Consulting - Quality

Difference makes the DIFFERENCE

SEABORN - SWARM PLOT Padhai ClassWork
Padhi_SwarmPlots

Swarm Plots, Strip Plots, Cat Plots

In [ ]:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(color_codes = True)
In [ ]:
df = sns.load_dataset('diamonds')
In [ ]:
df.head()
Out[ ]:
carat cut color clarity depth table price x y z
0 0.23 Ideal E SI2 61.5 55.0 326 3.95 3.98 2.43
1 0.21 Premium E SI1 59.8 61.0 326 3.89 3.84 2.31
2 0.23 Good E VS1 56.9 65.0 327 4.05 4.07 2.31
3 0.29 Premium I VS2 62.4 58.0 334 4.20 4.23 2.63
4 0.31 Good J SI2 63.3 58.0 335 4.34 4.35 2.75
In [ ]:
sns.swarmplot(x='caret')

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-4-00f5b161ca42> in <module>()
----> 1 sns.swarmplot(x='caret')

/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py in inner_f(*args, **kwargs)
     44             )
     45         kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
---> 46         return f(**kwargs)
     47     return inner_f
     48 

/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py in swarmplot(x, y, hue, data, order, hue_order, dodge, orient, color, palette, size, edgecolor, linewidth, ax, **kwargs)
   3003 
   3004     plotter = _SwarmPlotter(x, y, hue, data, order, hue_order,
-> 3005                             dodge, orient, color, palette)
   3006     if ax is None:
   3007         ax = plt.gca()

/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py in __init__(self, x, y, hue, data, order, hue_order, dodge, orient, color, palette)
   1170                  dodge, orient, color, palette):
   1171         """Initialize the plotter."""
-> 1172         self.establish_variables(x, y, hue, data, orient, order, hue_order)
   1173         self.establish_colors(color, palette, 1)
   1174 

/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py in establish_variables(self, x, y, hue, data, orient, order, hue_order, units)
    151                 if isinstance(var, str):
    152                     err = "Could not interpret input '{}'".format(var)
--> 153                     raise ValueError(err)
    154 
    155             # Figure out the plotting orientation

ValueError: Could not interpret input 'caret'
In [ ]:
sns.swarmplot(df.head(1000).carat)

/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.
  FutureWarning
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 44.4% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cfbe6cc90>
In [ ]:
sns.swarmplot(df.sample(500).carat)

/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.
  FutureWarning
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 13.6% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cfbc49050>
In [ ]:
sns.swarmplot(df.head(500).carat)

/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.
  FutureWarning
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 27.0% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cfccf4390>
In [ ]:
df.sample(50).head()
Out[ ]:
carat cut color clarity depth table price x y z
8932 1.01 Premium F SI2 61.6 58.0 4497 6.40 6.39 3.94
50158 0.52 Ideal D VVS2 59.9 57.0 2217 5.21 5.28 3.14
11971 1.01 Ideal F SI1 62.3 55.0 5140 6.37 6.44 3.99
40402 0.55 Ideal J VS2 60.4 58.0 1133 5.29 5.34 3.21
1941 0.90 Fair E SI2 64.5 55.0 3084 6.12 6.03 3.92
In [ ]:
df.sample(5)
Out[ ]:
carat cut color clarity depth table price x y z
6433 1.02 Fair G SI1 64.5 56.0 4044 6.30 6.23 4.04
324 1.00 Premium J SI2 62.3 58.0 2801 6.45 6.34 3.98
20875 1.59 Very Good G SI2 61.7 59.0 9094 7.41 7.46 4.59
46662 0.51 Ideal D VS2 60.9 56.0 1787 5.16 5.19 3.15
18669 1.12 Ideal G VS1 61.0 56.0 7632 6.76 6.72 4.11
In [ ]:
sns.swarmplot(df.sample(1000).price);

/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.
  FutureWarning
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 26.0% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
In [ ]:
sns.swarmplot(df.sample(1000).carat);

/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.
  FutureWarning
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 40.3% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)

by reducing the sample size to 100, may be more descriptive in graph

In [ ]:
sns.swarmplot(df.sample(100).price)

/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.
  FutureWarning
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cf73bd710>
In [ ]:
sns.swarmplot(df.sample(100).carat)

/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.
  FutureWarning
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cf73448d0>
In [ ]:
sns.kdeplot(df.sample(100).carat)
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cf8e3d950>
In [ ]:
sns.kdeplot(df.sample(100).price)
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cf72b4350>

In JOINT plot we have two continuous variables, where as here,

in SWARM Plots, we can have one continuous and the other to be categorical variable

In [ ]:
df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 53940 entries, 0 to 53939
Data columns (total 10 columns):
 #   Column   Non-Null Count  Dtype   
---  ------   --------------  -----   
 0   carat    53940 non-null  float64 
 1   cut      53940 non-null  category
 2   color    53940 non-null  category
 3   clarity  53940 non-null  category
 4   depth    53940 non-null  float64 
 5   table    53940 non-null  float64 
 6   price    53940 non-null  int64   
 7   x        53940 non-null  float64 
 8   y        53940 non-null  float64 
 9   z        53940 non-null  float64 
dtypes: category(3), float64(6), int64(1)
memory usage: 3.0 MB

sns.jointplot(x, y, data = df)

In [ ]:
df500 = df.sample(500)
In [ ]:
sns.jointplot(x = 'carat', y = 'price', data = df500)
Out[ ]:
<seaborn.axisgrid.JointGrid at 0x7f4cf4fb2dd0>
In [ ]:
sns.kdeplot(x='carat', y='price', data=df500)
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cf4cd2f10>
In [ ]:
sns.swarmplot(x='cut', y='price', data=df500);

/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 35.9% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 15.6% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 14.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
In [ ]:
sns.boxplot(x='carat', y='price', data=df500)
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cf48d9050>
In [ ]:
sns.boxplot(x='carat', data=df500)
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cf48e65d0>
In [ ]:
sns.boxplot(x = 'price', data=df500)
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cf3d7ee90>
In [ ]:
sns.swarmplot(x='cut', y = 'price', data=df500)

/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 35.9% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 15.6% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 14.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cf3d2ea90>
In [ ]:
df500.head(2)
Out[ ]:
carat cut color clarity depth table price x y z
11751 1.01 Premium E SI1 63.0 61.0 5077 6.42 6.37 4.03
46108 0.55 Very Good G VS1 62.8 57.0 1743 5.20 5.21 3.27
In [ ]:
sns.swarmplot(x='color', y='price', data=df500)

/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 13.6% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 33.7% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 26.4% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 28.9% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 24.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cf3cce210>
In [ ]:
sns.swarmplot(x="clarity", y = 'price', data=df500)

/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 23.8% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 25.0% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 27.9% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 30.9% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 27.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
/usr/local/lib/python3.7/dist-packages/seaborn/categorical.py:1296: UserWarning: 14.9% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.
  warnings.warn(msg, UserWarning)
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cf3c6c490>

Penguins dataset from Seaborn

In [ ]:
pen = sns.load_dataset('penguins')
In [ ]:
pen.head()
Out[ ]:
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex
0 Adelie Torgersen 39.1 18.7 181.0 3750.0 Male
1 Adelie Torgersen 39.5 17.4 186.0 3800.0 Female
2 Adelie Torgersen 40.3 18.0 195.0 3250.0 Female
3 Adelie Torgersen NaN NaN NaN NaN NaN
4 Adelie Torgersen 36.7 19.3 193.0 3450.0 Female
In [ ]:
sns.swarmplot(x=pen.species, y = pen.bill_length_mm, data = pen)
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cf1e5a090>
In [ ]:
sns.swarmplot(x=pen.island, y=pen.bill_length_mm, data=pen )
Out[ ]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f4cf3b8d990>