lab3

# coding: utf-8

# In[40]:


import numpy as np
import pandas as pd


# In[41]:


lables=['a','b','c']
my_list=[10,20,30]
arr=np.array([10,20,30])
d={'a':10,'b':20,'c':30}


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pd.Series(data=my_list)


# In[43]:


pd.Series(d)


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pd.Series([sum,print,len])


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ser1=pd.Series([1,2,3,4], index=['USA','Germany','USSR','Japan'])


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ser2=pd.Series([1,2,5,4], index=['USA','Germany','Italy','Japan'])


# In[49]:


ser1+ser2


# In[52]:


from numpy.random import randn
np.random.seed(101)


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df=pd.DataFrame(randn(5,4),index='A B C D E'.split(),columns = 'W X Y Z'.split())


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df


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df[['W','Z']]


# In[58]:


df.W


# In[59]:


type(df['W'])


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df['new']=df['W'] + df['Y']


# In[61]:


df


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df.drop('new',axis=1)


# In[64]:


df


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df.drop('new',axis=1,inplace=True)


# In[66]:


df


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df.drop('E',axis=0,inplace=True)


# In[68]:


df


# In[69]:


df.loc['A']


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df.loc['B','Y']


# In[71]:


df>0


# In[72]:


df


# In[75]:


df[df>0]


# In[79]:


df[df['W']>0]['Y']


# In[81]:


df[df['W']>0]


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df[df['W']>0][['Y','X']]


# In[85]:


df[(df['W']>0)& (df['Y']>0)]


# In[86]:


df.reset_index()


# In[109]:


newind='CA NY PL CA'.split()
df['States']=newind


# In[110]:


df


# In[112]:


df.set_index('States',inplace=True)


# In[113]:


df


# In[118]:


import matplotlib.pyplot as plt
from matplotlib import figure

df = pd.read_csv('C://Users//Admin//CSE_Avirup_Python/example.csv')
print(df)