from pandas import DataFrame as f
import numpy as np
import random
item = ['Onion', 'Sugar', 'Potato', 'Carrot'] * 5
place = ['Delhi'] * 4 + ['Bhopal'] * 4 + ['Bangalore'] * 4 + [
'Kolkata'
] * 4 + ['Mumbai'] * 4
total = random.sample(range(10, 50), 20)
df = f({'Item': item, 'Place': place, 'Total': total})
print df, "\n\n"
while True:
x = input(
"\n1.Display Itemwise Rank \n2.Display Itemwise Rank \n3.Exit\n>")
if x == 1:
it = raw_input("Enter the item Name : ")
il = df[df['Item'] == it]
il = il.copy()
tol = il['Total']
rank = tol.rank(ascending=False)
il['Rank'] = rank
print il
elif x == 2:
p = raw_input("Enter the place Name : ")
pl = df[df['Place'] == p]
pl = pl.copy()
tol = pl['Total']
rank = tol.rank(ascending=False)
pl['Rank'] = rank
print pl
else:
break
#!/usr/bin/python from pandas import Series as s from pandas import DataFrame as f import pandas as pd import numpy as np from matplotlib import pyplot as plt fsales = f(np.random.randint(1, 100, 20).reshape(5, 4)) fsales.index = 'apple orange grapes mango banana'.split() fsales.columns = 'Jan Feb Mar Apr'.split() so = fsales.plot(kind='bar', rot=45) print fsales plt.show()
import pandas as pd
from pandas import DataFrame as f
c = pd.read_csv('emp.csv')
ef1 = f(c)
ef1
a = ef1['ephno']
ef2 = f(a)
ef1 = ef1[['ename', 'eno', 'edesig', 'esalary']]
ef1
import pandas as pd
import numpy as np
from pandas import DataFrame as f
from pandas import Series as s
#Question 1 Create a (4,4)2D array consisting of integers.
a = np.array(range(1, 17)).reshape(4, 4)
#Question 2 Create a masked array from the above array by making numbers which are divisible by 3 as invalid values.
mska = np.ma.masked_array(a, mask=a % 3 == 0)
print mska.mask, "\n"
#Question 3 Create a dataframe from the above masked array.
dfma = f(mska)
print dfma, "\n"
#Question 4 Create a series of your own choice and do reindexing by exploring ffill,bfill,nearest etc
s1 = s(range(4), index=list("abcd"))
print s1, "\n"
print s1.reindex(list("abcde")), "\n"
print s1.reindex(list("abcde"), method="ffill"), "\n"
print s1.reindex(list("abcde"), method="bfill"), "\n"
#print s1.reindex(list("abecd"),method="nearest"),"\n"
#Question 5 Create a Dataframe object of your own choice and do reindexing.
ad = np.arange(1, 10).reshape(3, 3)
df1 = f(ad, columns=list("abc"), index=list("xyz"))
print df1, "\n"
print df1.reindex(list("yzx")), "\n"
#Question 6 Create a dataframe object from the above array by making c1,c2,c3,c4 as column indices and r1,r2,r3,r4 as row indices.
print(b)
'''
#--------------------------------------------------
import numpy as np
import pandas as pd
from pandas import DataFrame as f
global d
d = {'Item':['a','b','c','e'],\
'Place':['MH','KL','JK','TN'],\
'Total sale':[100,200,500,300]}
global df
df = f(d)
def ItemWise():
print(df)
p = input('enter a item name :')
for i, j in zip(df.index, df['Item']):
if j == p:
print('Place Wise rank of ', p, ' is ', df.rank()['Place'][i])
def placeWise():
print(df)
q = input('enter a place name: ')
import pandas as pd
from pandas import DataFrame as f
import numpy as np
df = f(np.random.randint(10, 20, 40).reshape(10, 4),
columns="c1 c2 c3 c4".split())
print df
print df.sort_values(['c1', 'c3'], ascending=[True, False])
