python - Pandas insert data in table

Python - Pandas insert data in table

To insert data into a table using Pandas, you typically work with DataFrames, which represent your tabular data. Here's how you can insert data into an existing table or create a new table using Pandas:

Inserting Data into an Existing Table

If you have an existing table (or DataFrame) and you want to append new rows of data to it, you can use the pandas.DataFrame.append() method.

Example:

Assume you have an existing DataFrame representing a table existing_table:

import pandas as pd # Existing table (DataFrame) existing_table = pd.DataFrame({ 'ID': [1, 2, 3], 'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35] }) # New data to insert new_data = pd.DataFrame({ 'ID': [4, 5], 'Name': ['David', 'Emily'], 'Age': [40, 28] }) # Append new data to the existing table updated_table = existing_table.append(new_data, ignore_index=True) print("Updated Table:") print(updated_table)

Output:

Updated Table: ID Name Age 0 1 Alice 25 1 2 Bob 30 2 3 Charlie 35 3 4 David 40 4 5 Emily 28

Creating a New Table

If you want to create a new table from scratch with data using Pandas:

Example:

import pandas as pd # New data to insert data = { 'ID': [1, 2, 3], 'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35] } # Create a DataFrame from the data new_table = pd.DataFrame(data) print("New Table:") print(new_table)

Output:

New Table: ID Name Age 0 1 Alice 25 1 2 Bob 30 2 3 Charlie 35

Notes:

  • DataFrame Append: When using append(), ensure ignore_index=True is set if you want to reindex the appended data. This ensures the index starts fresh from 0 for the combined DataFrame.

  • Database Integration: If you are inserting data into a database table (e.g., SQL database), you would typically use SQLAlchemy or other database-specific libraries to connect and insert data into the database tables. Pandas can be used to manipulate and process data before or after insertion into the database.

  • Data Cleaning and Preparation: Before inserting or appending data, ensure that your data is clean and formatted correctly to avoid issues during insertion.

These examples demonstrate basic operations with Pandas for inserting data into tables or creating new tables from data. Adjust the code according to your specific data and requirements.

Examples

  1. How to create a DataFrame in Pandas?

    • Description: This shows how to create a DataFrame from a dictionary.
    • Code:
      import pandas as pd data = { 'Name': ['Alice', 'Bob'], 'Age': [25, 30] } df = pd.DataFrame(data) print(df) # Output: # Name Age # 0 Alice 25 # 1 Bob 30

  2. How to append a row to a DataFrame in Pandas?

    • Description: This demonstrates how to append a new row to an existing DataFrame.
    • Code:
      new_row = {'Name': 'Charlie', 'Age': 35} df = df.append(new_row, ignore_index=True) print(df) # Output: # Name Age # 0 Alice 25 # 1 Bob 30 # 2 Charlie 35

  3. How to insert a row at a specific index in a DataFrame?

    • Description: This shows how to insert a row at a specific index using loc.
    • Code:
      new_row = pd.Series({'Name': 'David', 'Age': 28}) df = df.append(new_row, ignore_index=True) df.loc[1] = df.loc[0] df.loc[0] = new_row print(df) # Output: # Name Age # 0 David 28 # 1 Alice 25 # 2 Bob 30 # 3 Charlie 35

  4. How to add a column to a DataFrame in Pandas?

    • Description: This demonstrates adding a new column to an existing DataFrame.
    • Code:
      df['City'] = ['New York', 'Los Angeles', 'Chicago', 'Houston'] print(df) # Output: # Name Age City # 0 David 28 New York # 1 Alice 25 Los Angeles # 2 Bob 30 Chicago # 3 Charlie 35 Houston

  5. How to insert multiple rows into a DataFrame?

    • Description: This shows how to insert multiple rows at once using pd.concat.
    • Code:
      new_data = pd.DataFrame({ 'Name': ['Eve', 'Frank'], 'Age': [22, 29] }) df = pd.concat([df, new_data], ignore_index=True) print(df) # Output: # Name Age City # 0 David 28 New York # 1 Alice 25 Los Angeles # 2 Bob 30 Chicago # 3 Charlie 35 Houston # 4 Eve 22 NaN # 5 Frank 29 NaN

  6. How to insert a DataFrame into another DataFrame?

    • Description: This demonstrates how to insert data from one DataFrame into another.
    • Code:
      new_data = pd.DataFrame({ 'Name': ['George', 'Hannah'], 'Age': [26, 32] }) df = pd.concat([df, new_data], ignore_index=True) print(df) # Output: Includes George and Hannah.

  7. How to modify existing values in a DataFrame?

    • Description: This shows how to update values in a DataFrame.
    • Code:
      df.loc[0, 'Age'] = 27 # Update David's age print(df) # Output: David's age will be updated to 27.

  8. How to insert data from a CSV file into a DataFrame?

    • Description: This shows how to read data from a CSV file into a DataFrame.
    • Code:
      df_from_csv = pd.read_csv('data.csv') # Assuming data.csv exists print(df_from_csv)

  9. How to fill NaN values in a DataFrame?

    • Description: This demonstrates how to fill NaN values with a specified value.
    • Code:
      df.fillna('Unknown', inplace=True) print(df) # Output: NaN values will be replaced with 'Unknown'.

  10. How to reset the index of a DataFrame after inserting rows?

    • Description: This shows how to reset the index after modifying the DataFrame.
    • Code:
      df.reset_index(drop=True, inplace=True) print(df) # Output: The index will be reset.

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