Python Pandas 2

Question 1

Line to read a CSV file

Answer 1

import pandas as pd

df=pd.read_csv(“k.csv”)

Question 2

What does df.head(3) do ?

Answer 2

Prints the first 3 entires

Question 3

What does df.tail(3) do ?

Answer 3

Fetches the last 3 entries of all entries

Question 4

What is the line to read excel sheets

Answer 4

excel_data_df = pandas.read_excel(‘records.xlsx’, sheet_name=’Employees’)

Question 5

How do you read a file that ISNT CSV but has different delimitter? 8:18

Answer 5

df = pd.read_csv(“pk_data.txt”.delimiter=’\t’ )

Question 6

Line to get names of all columns in the data file

Answer 6

df.columns

Question 7

Line to print one certain column

Answer 7

dt[‘Col_Name’]

Question 8

Line to get specific column of top 5 entries

Answer 8

dt[‘Col’][0:5]

Question 9

Line to get multple selective columns

Answer 9

dt[[‘Col1’,’Col2’]]

Question 10

Line to get all details concerning row at certain position

Answer 10

df.iloc[1]

(Getting entry at position 2 zero indexing applies)

Question 11

Line to get all details concerning multiple first few row

Answer 11

df.iloc[0:2]

Question 12

Line to get a specific column OF a certain entry using ONLY INDICES

Answer 12

df.iloc[1,2]

1 is the second entry

And 2 stands for the 3rd column (We have to account for the zero indexing)

Question 13

Line to iterate through all entries of datasheet

Answer 13

for index,df in df.iterrows():
print(index,df)

/////df stands for data frame/////

Question 14

Line to iterate through rows and print specific columns of those entries

Answer 14

for index,df in df.iterrows():
print(index,df[‘Name’])

Question 15

Line to to fetch data entries that satisfy a certain condition(Search filters).

Answer 15

df. loc[df[‘Type 1’] == Grass]
df. loc[‘Type 1’] returns all data strings under Type 1 column and then the condition checks which of them are ‘Grass’

Question 16

Line to fetch data that has multiple filter layers

Answer 16

df.loc[df[‘Type 1’] == Grass].loc[df[‘Type 1’] == Fire]]

Question 17

Line to get standard deviation of a certain column

Answer 17

df[‘Age’].describe()[‘std’]

Question 18

What is the use of describe() is pandas

Answer 18

It displays data like count ,mean , min , std, 25percent, 75 and max

Question 19

Sort values in ascending order

Answer 19

df.sort_values(‘Power’)

Question 20

Sort names in leographic order

Answer 20

df.sort_values(‘Name’)

Question 21

Sort elements in descending order

Answer 21

df.sort_values(‘Name’,ascending = False)

Question 22

Sort first column with ascending and second column with desc

Answer 22

df.sort_values([‘Type1’,’HP’],ascending=[1,0])

Question 23

Line to Create new column which is function of previous columns

Answer 23

df[‘Total’] = df[‘HP’]+df[‘Attack’]-df[‘Damage’]

/////It automatically creates a new column for the rest ////

Question 24

Remove muliple columns

Answer 24

df = df.drop(columns = [‘Total1’,’Total2’])

Question 25

Getting stats for specific column

Answer 25

df[“Age”].describe()

Question 26

What does descibe function of pandas dataframe return me ?

Answer 26

It returns me a dictionary of various quantites

Question 27

Line to get a specific column (VIA LABEL) OF a certain entry (VIA INDEX)

Answer 27

first = data.iloc[0][‘Age’]

We used 0 as index for entry (Meaning first row ) and label as identifier for specific column (Age is the column)

Question 28

Line to get standard deviation of all columns

Answer 28

df.describe()[‘std’]

Question 29

Error debugging #1

What happens if you write print(df[Name])

Answer 29

It will raise an error because in df[Name] we should pass a stiring, not just Name(Which might work if it was defined as a string var)

Question 30

What is the difference between iloc and loc functions ?

Answer 30

loc is used for fetching entires based on boolean conditions

whereas

iloc is used for fetching results based on simple indices.

(Hence the use of i, which probably means index locator)

Question 31

Line for filtering data of a certain column using indexof column BUT NOT LABEL

Answer 31

df.loc[df.iloc[:,6]

Question 32

Line for printing specific entires based on comparision filters

Answer 32

df[df[‘Col1’]

Question 33

Line for printing specific columns AFTER performing a search criteria

Answer 33

df.loc[df[‘Units’]

Question 34

Line to replace all entries that contain specific element(string or value) with a DIFFERENT element

Answer 34

df.replace(to_replace =”Boston Celtics”,value =”Omega Warrior”)

Question 35

Line to replace all entries that contain specific element (string or value) that belong to a set with a DIFFERENT element

Answer 35

df.replace(to_replace =[“Boston Celtics”, “Texas”], value =”Omega Warrior”)