Create a new dataframe pandas

Here is an example of how to create a new Pandas DataFrame:

import pandas as pd

# Create a dictionary to store the data
data = {'Name': ['John', 'Mary', 'David', 'Emily'],
        'Age': [25, 31, 42, 28],
        'City': ['New York', 'Los Angeles', 'Chicago', 'Houston']}

# Create a Pandas DataFrame from the dictionary
df = pd.DataFrame(data)

print(df)

This will output:

     Name  Age           City
0    John   25     New York
1    Mary   31  Los Angeles
2   David   42      Chicago
3   Emily   28      Houston

You can also create a DataFrame from a list of dictionaries:

data = [{'Name': 'John', 'Age': 25, 'City': 'New York'},
        {'Name': 'Mary', 'Age': 31, 'City': 'Los Angeles'},
        {'Name': 'David', 'Age': 42, 'City': 'Chicago'},
        {'Name': 'Emily', 'Age': 28, 'City': 'Houston'}]

df = pd.DataFrame(data)
print(df)

This will output the same result as above.

You can also create a DataFrame from a NumPy array:

import numpy as np

data = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])

df = pd.DataFrame(data, columns=['A', 'B', 'C'])
print(df)

This will output:

You can also create a DataFrame from a CSV file:

df = pd.read_csv('data.csv')
print(df)

This will read the data from the file data.csv and create a DataFrame from it.

You can also create a DataFrame from a SQL database:

import pandas as pd
import sqlite3

conn = sqlite3.connect('database.db')
df = pd.read_sql_query('SELECT * FROM table_name', conn)
print(df)

This will read the data from the table table_name in the database database.db and create a DataFrame from it.

These are just a few examples of how to create a new Pandas DataFrame. There are many other ways to create a DataFrame, depending on the type of data you have and the format you want to use.

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Create a new dataframe pandas