bhishanpdl

from IPython.display import Markdown, display

def printmd(string, color=None):
    colorstr = "<span style='color:{}'>{}</span>".format(color, string)
    display(Markdown(colorstr))

printmd("**bold and blue**", color="blue")

bhishanpdl

ls dir1/dir2/*.txt | xargs -n 1 basename

bhishanpdl

.apply(pd.to_numeric,errors='coerce')

bhishanpdl

import numpy as np
import matplotlib.pyplot as plt
from numpy.random import random

t = np.linspace(0, 1, 101)

plt.figure()
plt.subplot(2, 2, 1); plt.hist(random(20))
plt.subplot(2, 2, 2); plt.plot(t, t**2, t, t**3 - t)
plt.subplot(2, 2, 3); plt.plot(random(20), random(20), 'r*')

bhishanpdl

t = np.linspace(0, 5*np.pi, 501) # Define parameter for parametric plot.
plt.plot(t, np.sin(t)**2) # Generate plot.
plt.plot(t, np.sin(t)**3) # Create new plot on same axes.
ax = plt.gca() # Gain control of axes.
ax.hold(False) # Turn hold off.
plt.plot(t, np.sin(t)**4) # Create new plot; old data erased.

bhishanpdl

data = [[2000, 2000, 2000, 2001, 2001, 2001, 2002, 2002, 2002],
        ['Jan', 'Feb', 'Mar', 'Jan', 'Feb', 'Mar', 'Jan', 'Feb', 'Mar'],
        [1, 2, 3, 4, 5, 6, 7, 8, 9]]

rows = list(zip(data[0], data[1], data[2]))
headers = ['Year', 'Month', 'Value']
df = pd.DataFrame(rows, columns=headers)

pivot_df = df.pivot(index='Year', columns='Month', values='Value')

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df.set_index('First_col').T.plot(kind='bar', stacked=True,figsize=(16,8))

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%matplotlib inline

from pandas import Series
import matplotlib.pyplot as plt

heights = Series(
    [165, 170, 195, 190, 170, 
     170, 185, 160, 170, 165, 
     185, 195, 185, 195, 200, 
     195, 185, 180, 185, 195],

bhishanpdl

import pandas as pd
import string

df = pd.DataFrame({'c0':range(1,10), 'c1': list(string.ascii_letters[0:9])})
df2 = df.iloc[[0, -1]]

# first and last 10
df = pd.concat([df.head(10), df.tail(10)])

bhishanpdl

import pandas as pd
import calendar

# Ref: https://docs.python.org/2/library/datetime.html


df['release_year'] = pd.to_datetime(df['release_date'], format='%m/%d/%y')

df['release_month'] = df['release_year'].dt.month