HANDLING MISSING DATA (FillNa) IN PANDAS

Firstly, we are importing an excel sheet as a DataFrame,

 

import pandas as pd

ds = pd.read_excel("C:\\Users\\mahes\\OneDrive\\Documents\\Students.xlsx")

dt = pd.DataFrame(ds)

print(dt)

Now, Let's perform some operations related to FillNa()

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HANDLING MISSING DATA (dropna) IN PANDAS

Firstly, we are importing an excel sheet as a DataFrame,

 

import pandas as pd

ds = pd.read_excel("C:\\Users\\mahes\\OneDrive\\Documents\\Students.xlsx")

dt = pd.DataFrame(ds)

print(dt)

Now, Let's perform some operations related to DROPNA

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ILOC[ ] IN PANDAS - PYTHON

Firstly, we are importing an excel sheet as a DataFrame,

 

import pandas as pd

ds = pd.read_excel("C:\\Users\\mahes\\OneDrive\\Documents\\Students.xlsx")

dt = pd.DataFrame(ds)

Now, Let's perform some operations related to ILOC 

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LOC[ ] IN PANDAS - PYTHON

LOC[ ] IN PANDAS

Firstly, we are importing an excel sheet as a DataFrame,

 

import pandas as pd

ds = pd.read_excel("C:\\Users\\mahes\\OneDrive\\Documents\\Students.xlsx")

dt = pd.DataFrame(ds)

Now, Let's perform some operations related to LOC and ILOC 

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EXPORT DATAFRAME TO EXCEL, CSV & TEXT FILE IN PANDAS || SAVE DATAFRAME IN PANDAS

EXPORT DATAFRAME TO EXCEL, CSV & TEXT FILE IN PANDAS 

Firstly, we are importing an excel sheet as a DataFrame,

 

import pandas as pd

st = pd.read_excel("C:\\Users\\mahes\\OneDrive\\Documents\\Students.xlsx")

sd = pd.DataFrame(st)

print(st)

Making some changes in the dataframe

st['Total']=st['Hindi']+st['English'] +st['Science'] +st['History']+st['Mathematics']

Now, exporting the DataFrame as Excel, CSV and Text File

sd.to_excel("C:\\Users\\mahes\\OneDrive\\Desktop\\StudentsNew.xlsx")

sd.to_csv("C:\\Users\\mahes\\OneDrive\\Desktop\\StudentsNew.csv")

sd.to_csv("C:\\Users\\mahes\\OneDrive\\Desktop\\StudentsNew.txt" ,sep = "\t")

As you can see we have created three new files.

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SORTING DATAFRAME (BY COLUMN) IN PANDAS (Part-2) - PYTHON PROGRAMMING

#SORTING DATAFRAME (BY COLUMN) IN PANDAS (Part-2) - PYTHON PROGRAMMING

Listing Two Rows

df[['Name','Total_Marks']]

df = df.drop(columns = "Total_Marks")

print(df)

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MANIPULATING DATAFRAME IN PANDAS (ADD COLUMN , DROP COLUMN) || DATAFRAME MANIPULATIONS

import pandas as pd 

dt = pd.read_excel("C:\\Users\\mahes\\OneDrive\\Documents\\Students.xlsx")

df = pd.DataFrame(dt)

print(df)

df['Total_Marks'] = 0

print(df)

df['Total_Marks'] = df['Hindi']+df['English']

df

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SORTING DATAFRAME (BY COLUMN) IN PANDAS - PYTHON PROGRAMMING

#SORTING DATAFRAME (BY COLUMN) IN PANDAS 

#clcoding

import pandas as pd

dt = pd.read_excel("FILE_NAME")

print(dt)

df = pd.DataFrame(dt)

df.sort_values("MAXMTEMPERATURE", ascending = False)

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How do you generate random Password?

#How do you generate 8 random character?

#clcoding

from string import printable

from random import choice

print(*[choice(printable) for _ in range(8)], sep = '') 

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How do you reverse the string without take another string?

#How do you reverse the string without take another string?

#clcoding

s = 'hello'

n = -1

for x in s:

    n += 1

while n >= 0:

    print(s[n], end = '')

    n -= 1

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INDEXING & SLICING DATAFRAMES IN PANDAS [PART 3]- PYTHON PROGRAMMING

INDEXING & SLICING DATAFRAMES IN PANDAS

data_frame(start:step:stop)

data_frame(col_name)

data_frame(col_name)[index_value]

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INDEXING & SLICING DATAFRAMES IN PANDAS [PART 2]- PYTHON PROGRAMMING

INDEXING & SLICING DATAFRAMES IN PANDAS

Shape()

loc()

Columns()

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INDEXING & SLICING DATAFRAMES IN PANDAS [PART 1]- PYTHON PROGRAMMING

INDEXING & SLICING DATAFRAMES IN PANDAS

head( )

tail( )

describe( )

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MATHEMATICAL FUNCTIONS ON SERIES IN PANDAS [Part 1] - PYTHON PROGRAMMING

1] Addition 

#clcoding

import pandas as pd

s1 = pd.Series([10,20,30,40,50])

s2 = pd.Series([70,80,90,100,110])

 s1.add(s2)

2] Subtraction

import pandas as pd

s1 = pd.Series([10,20,30,40,50])

s2 = pd.Series([70,80,90,100,110])

s1.subtract(s2)

 

3] Multiplication

import pandas as pd

s1 = pd.Series([10,20,30,40,50])

s2 = pd.Series([70,80,90,100,110])

s1.multiply(s2)

4] Division

import pandas as pd

s1 = pd.Series([10,20,30,40,50])

s2 = pd.Series([70,80,90,100,110])

s1.divide(s2)

        

 

                                                                      

   

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OPERATIONS ON SERIES - PYTHON

ATTRIBUTES OF SERIES IN PANDAS

1. index 2. array 3. values 4. name 5. shape 6. size 7. nbytes 8. dtype 9. memory_usage( ) 10. empty 11. ndim

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ATTRIBUTES OF SERIES IN PANDAS - PYTHON PROGRAMMING

ATTRIBUTES OF SERIES IN PANDAS

Index - Series.index - Return all index values

Array - Series.array - Return all index values

Values - Series.values - Return values of series

Name - Series.name - Return the name of Series

Shape - Series.shape - Return the shape

Ndim - Series.ndim - Return the dimension of series

Size - Series.size - Return the size of series

Nbytes - Series.nbytes - Returns the memory occupied

memory-usage - Series.memory-usage() - Returns memory occupied by both index & values

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DIFFERENT WAYS OF CREATING DATAFRAME IN PANDAS - PYTHON PROGRAMMING TWO (II)

#clcoding

dt=[('a',10),('b',20),('c',30)]

pd.Series(dt)

df = pd.read_excel("FILE_NAME")

pd.DataFrame(df)

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DIFFERENT WAYS OF CREATING DATAFRAME IN PANDAS - PYTHON PROGRAMMING

#clcoding

import numpy as np

a = np.array([10,20,30,40,50])

import pandas as pd

sa = pd.Series(a)

print(a)

print(sa)

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How to find any vowels without using any loops

#How to find any vowels without using any loops

#clcoding

from re import findall

s = 'clcoding'

findall(r'[aeiou]',s)

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How do you find dayname of particular date of year?

#How do you find dayname of particular date of year?

#Clcoding

import calendar as cal

dayname = ['MONDAY', 'TUESDAY', 'WEDNESDAY', 'THURSDAY', 

          'FRIDAY', 'SATURDAY', 'SUNDAY']

inx = cal.weekday(2021,6,18)

dayname[inx]

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