Data Analyst

 Explain How to create a series from a list, numpy array and dict? import pandas as pd import numpy as np list = ["k","h","o","s","e"] Dict = {"k": 1,"h" : 2,"o" : 3,"s" :5,"e" :4} np = np.array(["k","h","o","s","e"]) print(pd.Series(list)) print("\n") print(pd.Series(Dict)) print("\n") print(pd.Series(np))

There are two ways an empty NumPy array can be created: numpy.zeros and numpy.empty . import numpy as np print(np.empty((4,4))) print("\n") print(np.zeros((4,4)))

Python has a built-in package called re , which can be used to work with Regular Expressions. Import the re module: import re. RegEx in Python. For our purpose, we will use the function search() , and then use group() to get the import re rhyme = re.search(".ake","I would like to make a cake") print(rhyme.group())  Out : 'make' And as we know, the function search() stops at the first match. Hence, we have our first rhyme to 'cake'.

import numpy as np #np.percentile(arr,n,axis= (1,0)) # n = percentile, 1= row, 0 = column arr = [10,20,30,40,50,60] print(np.percentile(arr,5)) # 2D  arr1 = [[10,20,30,40],[50,60,70,80]] print(np.percentile(arr1,5))

Numpy :  1. Creating numpy  2. Finding dimension, data type, shape,  reshape  3. Creating numpy with different way 4. Applying mathematics  5. Compared two array  6. Aggregate function  7. Array manipulations -- concatenate two array, stack array vstack and hstack, split two array 8. Sorting array import numpy as np  a = np.array([1,2,3,4]) b = np. array([5,6,7,8]) print(a.size) print("\n") print(a.ndim) print("\n") print(a.dtype) print("\n") print(a.shape) print("\n") print(np.linspace(1,10,2)) print("\n") print(np.arange(1,10,2)) print("\n") x = np.logspace(1,10,2) print(x) print("\n") print(np.zeros((4,2))) print("\n") print(np.ones((4,2))) print("\n") print(np.full((4,2),4)) print("\n") print(np.random.rand(2,4)) print("\n") print(np.sum([a,b],axis=0)) print("\n") print(np.subtract(a,b)) print("\n") print(np.multiply(a,b)) print(np.divide(a,b)) print(...

Pie Chart : import matplotlib.pyplot as plt a= ["apple","banana","mango"] b = [30,10,80] fig = plt.figure(figsize=(10,5)) plt.pie( b,labels=a, autopct = "%1.1f%%", shadow=True, startangle = 90 ) plt. show() Customizing Pie Chart : import matplotlib.pyplot as plt a= ["apple","banana","mango"] b = [30,10,80] fig = plt.figure(figsize=(10,5)) plt.pie(b,labels=a,autopct = "%1.1f%%" , shadow=True, startangle = 90, explode= (0.1,0.1,0) ) plt. show() Pie Chart Without Shadow : import matplotlib.pyplot as plt a= ["apple","banana","mango"] b = [30,10,80] fig = plt.figure(figsize=(10,5)) plt.pie(b,labels=a,autopct = "%1.1f%%", shadow= False , startangle = 90,     explode= (0.1,0.1,0)) plt. show() Donut Plot : import matplotlib.pyplot as plt name= ["kanchan" ,"kariahma","kajal",] marks = [80,85,90] center=[10] fig ...

Violin Plot : import matplotlib.pyplot as plt a = [1,2,35,9,10,15] b = [5,20,12,25,7,38] c= [3,7,18,22,14,31] data = list([a, b, c]) plt.violinplot(data, showmeans=True, showmedians = True ) plt.show() Customizing Violin Plot : import matplotlib.pyplot as plt a = [1,2,35,9,10,15] b = [5,20,12,25,7,38] c= [3,7,18,22,14,31] data = list([a, b, c]) fig = plt.figure(figsize=(10,5)) plt.violinplot(data,showmeans=True, showmedians = True) plt.legend() plt.grid(True) plt.xlabel("x") plt.ylabel("y") plt.show() Adding Two Violin Plot :  import matplotlib.pyplot as plt a = [1,2,35,9,10,15] b = [5,20,12,25,7,38] c= [3,7,18,22,14,31] a1 = [1,2,35,9,10,15] b1= [5,20,12,25,7,38] c1= [3,7,18,22,14,31] data = list([a, b, c]) data1 = list([a1, b1, c1]) fig = plt.figure(figsize=(10,5)) plt.subplot(1,2,1) plt.violinplot(data,showmeans=True, showmedians = True ) plt.legend() plt.grid(True) plt.xlabel("x") plt.ylabel("y...