Plotting a bar plot with DataFrame

For my class demo on 12 Jul 2018

## Concat
%matplotlib inline
import pandas as pd
import matplotlib.ticker as ticker
import matplotlib.pyplot as plt
import numpy as np

d1 = pd.read_csv("data/ura-private-district9.csv",skiprows=2)
d2 = pd.read_csv("data/ura-private-district3.csv",skiprows=2)

d = pd.concat([d1,d2])
d = d.rename(index=str,
            columns={"S/N":"SerialNumber","Price ($)":"Price", 
            "Project Name": "Project"})

d["SerialNumber"] = pd.to_numeric(d["SerialNumber"], errors="coerce")
d = d[~pd.isnull(d.Price)]
d["Unit Price ($psf)"] = pd.to_numeric(d["Unit Price ($psf)"], errors="coerce")
d["Date of Sale"] = pd.to_datetime(d["Date of Sale"], errors="coerce")

projects = d.groupby("Project")
medianpricebyproject = projects['Price'].median()
medianpricebyproject= pd.DataFrame(medianpricebyproject).sort_values(by=["Price"],

                                   ascending=False)
remover1 = lambda x: x.strip(' ').replace("\n","")
d_subset_01 = medianpricebyproject[medianpricebyproject.Price>5000000]
d_subset_01 = d_subset_01.sort_values(by=["Price"],ascending=False)

ax = d_subset_01.plot(kind="bar",figsize=(20,10))

from matplotlib.ticker import FuncFormatter
def millions(x, pos):
    'The two args are the value and tick position'
    return '$%1.1fM' % (x*1e-6)

formatter = FuncFormatter(millions)

ax.yaxis.set_major_formatter(formatter)

This is how it looks like: