How to write import-free syntax

#generate list
list = [0,1,2]
print(list)

[0, 1, 2]

#Add list

list2 = [[0,1,2]]
list2.append([3,4,5])
list2

[[0, 1, 2], [3, 4, 5]]

#list

len([0,1,2])

3

#list

[0,1,2].count(0)

1

#dictionary{key:value}Created in the format of
#Returns value when specified in method get

{"Miyasako" : "Honest", "Tamura" : "return"}.get("Miyasako")

'Shinshin'

#list specified in slice
#[:3]Specify from 0 to the third before

[0, 1, 2, 3, 4, 5][:3]

[0,1,2]

#How to make a UDF function

def printHello():
    return print("Hello, world!!")
 
printHello()

'Hello, world!!'

#Conditional branch in if statement

x = 10
if x <= 20:
    print("x is 20 or less.")
 
if x <= 30:
    print("x is 30 or less.")
 
elif x >=40:
    print("x is 40 or more.") #This sentence does not appear

'x is 20 or less. ' 'x is 30 or less. '

#for statement

x = 0
for i in range(100):
    x += i

4950

numpy module import

#Import numpy module
import numpy as np

example1 = np.array([2, 4, 6, 8, 10])
example1

array([ 2, 4, 6, 8, 10])

#print("{}".format())Can be commented so it is easy to check the contents

print("example1:\n{}".format(example1))

example1: [ 2 4 6 8 10]

#If you pass a nested list

example2 = np.array([[1, 2, 3, 4, 5], [2, 4, 6, 8, 10]])
example2

array( [[ 1, 2, 3, 4, 5], [ 2, 4, 6, 8, 10]])

#Dimension and shape of example2
#Note that shape cannot be used for list! Let's put it in ndarray

print(example2.ndim, example2.shape)

2 (2, 5)

#Matrix permutation

example2.transpose()

array( [[ 1, 2], [ 2, 4], [ 3, 6], [ 4, 8], [ 5, 10]])

#ndarray → list conversion

np.array([1,2,3,4,5][2,3,4,5,6]).tolist()

pandas module import

#Import pandas module
import pandas as pd

data = pd.DataFrame({"area" : [18, 19, 20], "age" : [5, 4, 10]}, index = ["A", "B", "C"])
data

#Refer to only the first n lines of the data frame.
data.head(1)

#Numpy array of values from the dataframe/Get a numpy array of column names.
data.values, data.columns

(array([ [ 5, 18], [ 4, 19], [10, 20]]), Index(['age', 'area'], dtype='object'))

#Summary statistics
data.describe()

#Correlation coefficient
data.corr()

#Delete column
data = data.drop("time", axis = 1)
data

#Column selection
data[["age","area"]]

#Condition specification
data[(data["age"]<=5) & (data["area"]==18)]

# ndarray→dataframe

A = np.array([[1,2],[2,3],[3,4]])
 
#cloumns naming
B = pd.DataFrame(A,columns={"NO_1","NO_2"})
  
#columns renamed
B.rename(columns={"NO_1":"no1","NO_2":"no2"})

#Aggregate
B.groupby("NO_1",as_index=False).sum()

python memorandum super basic

How to write import-free syntax