import pandas as pd

data = {
    'Month' : [1, 2, 3],
    'Temp' : [7, -18, -20]
}

data

{'Month': [1, 2, 3], 'Temp': [7, -18, -20]}

type(data)

dict

df = pd.DataFrame(data)

df

import numpy as np

# Create a 2D array
a = np.array([[1, 2, 3],
              [4, 5, 6],
              [7, 8, 9]])

print("Original Array:")
print(a)

# Slice a specific row
print("\nFirst row:")
print(a[0])

# Slice a specific column
print("\nSecond column:")
print(a[:, 1])

# Slice a sub-matrix …

print("hello")

hello

import logging
import pandas as pd
import numpy as np
from numpy import random
import gensim
import nltk
from sklearn.model_selection import train_test_split
from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer

from sklearn.metrics import accuracy_score, confusion_matrix
import matplotlib.pyplot as plt
from nltk.corpus import stopwords
import re
from bs4 …

import pandas as pd
import numpy as np

from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression, LinearRegression
from sklearn.neighbors import KNeighborsClassifier
from sklearn.svm import SVC
from sklearn.naive_bayes import GaussianNB
from sklearn.neural_network import MLPClassifier
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import RandomForestClassifier
from …

import pyutil as pyu
pyu.get_local_pyinfo()

'conda env: C:\\Users\\Afia Jahan\\anaconda3\\envs\\py312; pyv: 3.12.11 | packaged by Anaconda, Inc. | (main, Jun  5 2025, 12:58:53) [MSC v.1929 64 bit (AMD64)]'

print(pyu.ps2("yfinance pandas matplotlib"))

import yfinance as yf
import pandas as pd …