python - Seaborn Barplot - Displaying Values

Question

I'm looking to see how to do two things in Seaborn with using a bar chart to display values that are in the dataframe, but not in the graph

1) I'm looking to display the values of one field in a dataframe while graphing another. For example, below, I'm graphing 'tip', but I would like to place the value of 'total_bill' centered above each of the bars (i.e.325.88 above Friday, 1778.40 above Saturday, etc.)

2) Is there a way to scale the colors of the bars, with the lowest value of 'total_bill' having the lightest color (in this case Friday) and the highest value of 'total_bill' having the darkest. Obviously, I'd stick with one color (i.e. blue) when I do the scaling.

Thanks! I'm sure this is easy, but i'm missing it..

While I see that others think that this is a duplicate of another problem (or two), I am missing the part of how I use a value that is not in the graph as the basis for the label or the shading. How do I say, use total_bill as the basis. I'm sorry, but I just can't figure it out based on those answers.

Starting with the following code,

import pandas as pd
import seaborn as sns
%matplotlib inline
df=pd.read_csv("https://raw.githubusercontent.com/wesm/pydata-    book/master/ch08/tips.csv", sep=',')
groupedvalues=df.groupby('day').sum().reset_index()
g=sns.barplot(x='day',y='tip',data=groupedvalues)

I get the following result:

Interim Solution:

for index, row in groupedvalues.iterrows():
    g.text(row.name,row.tip, round(row.total_bill,2), color='black', ha="center")

On the shading, using the example below, I tried the following:

import pandas as pd
import seaborn as sns
%matplotlib inline
df=pd.read_csv("https://raw.githubusercontent.com/wesm/pydata-book/master/ch08/tips.csv", sep=',')
groupedvalues=df.groupby('day').sum().reset_index()

pal = sns.color_palette("Greens_d", len(data))
rank = groupedvalues.argsort().argsort() 
g=sns.barplot(x='day',y='tip',data=groupedvalues)

for index, row in groupedvalues.iterrows():
    g.text(row.name,row.tip, round(row.total_bill,2), color='black', ha="center")

But that gave me the following error:

AttributeError: 'DataFrame' object has no attribute 'argsort'

So I tried a modification:

import pandas as pd
import seaborn as sns
%matplotlib inline
df=pd.read_csv("https://raw.githubusercontent.com/wesm/pydata-book/master/ch08/tips.csv", sep=',')
groupedvalues=df.groupby('day').sum().reset_index()

pal = sns.color_palette("Greens_d", len(data))
rank=groupedvalues['total_bill'].rank(ascending=True)
g=sns.barplot(x='day',y='tip',data=groupedvalues,palette=np.array(pal[::-1])[rank])

and that leaves me with

IndexError: index 4 is out of bounds for axis 0 with size 4

Answer 1

Works with single ax or with matrix of ax (subplots)

from matplotlib import pyplot as plt
import numpy as np

def show_values_on_bars(axs):
    def _show_on_single_plot(ax):        
        for p in ax.patches:
            _x = p.get_x() + p.get_width() / 2
            _y = p.get_y() + p.get_height()
            value = '{:.2f}'.format(p.get_height())
            ax.text(_x, _y, value, ha="center") 

    if isinstance(axs, np.ndarray):
        for idx, ax in np.ndenumerate(axs):
            _show_on_single_plot(ax)
    else:
        _show_on_single_plot(axs)

fig, ax = plt.subplots(1, 2)
show_values_on_bars(ax)