nithyadurai87

import pandas as pd
from datetime import datetime,timedelta
import numpy as np

df = pd.read_csv('./13_input_data.csv')
print (df)

pd.set_option("display.max_columns",8) 

df1 = pd.DataFrame()

nithyadurai87

import pandas as pd

d = {'Names' : pd.Series(['Mahesh','Yazhini','Kadiresan','Malathi','Kumar','Sujith']), 
'Gender' : pd.Series(['Male','Trans','Male','Female','Male','Trans'],dtype="category")}
df = pd.DataFrame(d)

print (df['Names'])
print (df['Gender'])
print (df['Gender'].cat.remove_categories(['Trans'])) # add_categories()
print (df['Gender'].cat.categories)

nithyadurai87

import pandas as pd

df = pd.DataFrame({'Name':['Mahesh','Elango','Kadiresan','Sundar','Kumar'],'Joining_date':['2020.01.14', '2020, 12, 23', 'Nov 19, 2020', '2020, 04, 06','2020.06.30']})
print (df)

df['Joining_date'] = pd.to_datetime(df['Joining_date'])
print (df)

df['confirmation_date'] = df['Joining_date']+pd.Timedelta(days=180)
print (df)

nithyadurai87

import pandas as pd
import numpy as np

l2 = [[90,83,67,83,45],[68,89,75,56,73],[58,88,60,90,100]]
df = pd.DataFrame(l2,columns=['Tamil','English','Maths','Science','Social'],index=['Ramesh','Suresh','Kamesh'],dtype='int32')

df = df.rolling(window=3).mean()
print (df)
print (df.isnull())
print (df.notnull())

nithyadurai87

import pandas as pd
import numpy as np

l2 = [[90,83,67,83,45],[68,89,75,56,73],[58,88,60,90,100]]
df = pd.DataFrame(l2,columns=['Tamil','English','Maths','Science','Social'],index=['Ramesh','Suresh','Kamesh'],dtype='int32')

print (df)
print (df.pct_change())
print (df['Tamil'].cov(df['English']))
print (df.cov())

nithyadurai87

import pandas as pd
import numpy as np

l2 = [[90,83,67,83,45],[68,89,75,56,73],[58,88,60,90,100]]
df = pd.DataFrame(l2,columns=['Tamil','English','Maths','Science','Social'],index=['Ramesh','Suresh','Kamesh'],dtype='int32')

for i in df:
    print (i)
    
for i in df.itertuples():

nithyadurai87

import pandas as pd

df = pd.read_csv("./girls.csv")
print (df)

print (df.head())
print (df.head(2))

print (df[df['place'] == 'Hyderabad'])

nithyadurai87

import pandas as pd

df = pd.read_csv("./girls.csv")
print (df.shape)
print (df.columns)
print (df['fname']) # df.fname , df['fname','age'] 

print (df.loc[ 1:4 , 'fname' ])
print (df.loc[ [1,4] , 'fname' ])
print (df.loc[ : , 'age']>30 )

nithyadurai87

import pandas as pd

df = pd.DataFrame({'Languages': pd.Series(['Tamil','English']), 'Subjects': pd.Series(['Maths','Science','Social'])})
print (df)
print (df['Languages'].str.upper()) # lower(), swapcase(), islower(), isupper(), isnumeric()
print (df['Languages'].str.split('i'))
print (df['Languages'].str.contains('i'))
print (df['Languages'].str.len())
print (df['Subjects'].str.startswith('S')) # endswith()
print (df['Subjects'].str.count('e'))

nithyadurai87

import pandas as pd

s = pd.Series([90,83,67,83,45])
df = pd.DataFrame([[90,83,67,83,45],[68,89,75,56,73],[58,88,60,90,100]])
p = pd.Panel({'Midterm': pd.DataFrame([[90,83,67,83,45],[68,89,75,56,73],[58,88,60,90,100]]), 
'Quarterly': pd.DataFrame([[35,44,65,56,79],[85,55,84,50,99],[65,90,87,69,78]])})

print (s.axes)
print (df.axes)
print (p.axes)