Import CSV with Pandas in Micronugget 📊

Download 1M+ code from https://codegive.com/bde4150
sure! micronugget is a lightweight python library designed to simplify data manipulation and analysis tasks. in this tutorial, we will focus on how to import data from a csv file using the pandas library, which is a powerful and widely-used library for data analysis in python.

tutorial: importing data from a csv file with pandas

prerequisites

- python installed on your machine (preferably version 3.6 or later)
- pandas library installed (`pip install pandas`)
- a csv file that you want to import (we'll create a sample one for demonstration)

step 1: create a sample csv file

for demonstration purposes, let's create a sample csv file named `sample_data.csv`. you can create this file using a text editor and add the following content:



save this file in your project directory.

step 2: import pandas library

now, let's write a python script to import the pandas library and read the csv file.



step 3: read the csv file

you can read the csv file using the `pd.read_csv()` function. here’s how to do it:



full code example

here’s the complete code that you can run in your python environment:



step 4: running the code

1. save the code in a file named `import_csv_example.py`.
2. make sure that `sample_data.csv` is in the same directory as your python script.
3. run the script using the command line:



output

when you run the script, you should see the following output:



additional options

the `pd.read_csv()` function has several optional parameters that you can use to customize the reading process:

- **`sep`**: specify a different delimiter (default is `,`).
- **`header`**: specify row number to use as column names (default is the first row).
- **`index_col`**: specify column(s) to set as index (default is `none`).
- **`usecols`**: specify which columns to read.
- **`dtype`**: specify data types for columns.

example with additional options

here’s an example that uses some of these options:



this code will read only the `name` and `city` colum ...

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