Project Description:

Title: Pandas Data Manipulation and File Conversion

Overview: This project aims to demonstrate the basic functionalities of Pandas, a powerful data manipulation library in Python. In this project, we will create a DataFrame, perform some data manipulation operations using Pandas, and then convert the DataFrame into both Excel and CSV formats.

Key Objectives:

1. DataFrame Creation: Utilize Pandas to create a DataFrame with sample data.
2. Data Manipulation: Perform basic data manipulation tasks such as adding columns, filtering data, and performing calculations.
3. File Conversion: Convert the DataFrame into Excel (.xlsx) and CSV (.csv) file formats.

Tools and Libraries Used:

• Python
• Pandas

Project Implementation:

1. DataFrame Creation:

   • Import the Pandas library.
   • Create a DataFrame using either a dictionary, a list of dictionaries, or by reading data from an external source like a CSV file.
   • Populate the DataFrame with sample data representing various data types (e.g., integer, float, string, datetime).

2. Data Manipulation:

   • Add new columns to the DataFrame representing derived data or computations based on existing columns.
   • Filter the DataFrame to include only specific rows based on certain conditions.
   • Perform basic calculations or transformations on the data, such as aggregation functions or arithmetic operations.

3. File Conversion:

   • Utilize Pandas to convert the DataFrame into an Excel (.xlsx) file using the to_excel() function.
   • Convert the DataFrame into a CSV (.csv) file using the to_csv() function.
   • Save the generated files to the local file system for further analysis or sharing.

Expected Outcome:

Upon completion of this project, you will have gained a fundamental understanding of how to work with Pandas DataFrames, perform basic data manipulation tasks, and convert DataFrames into different file formats. This knowledge will be valuable for data analysis, preprocessing, and data export tasks in various data science and analytics projects.

Conclusion:

The Pandas library offers powerful tools for data manipulation and file conversion in Python. By completing this project, you will have acquired essential skills that are widely applicable in the field of data science and analytics. You can further extend this project by exploring more advanced Pandas functionalities or integrating it into larger data processing pipelines.in this data we add number of data and make that data a data frame.and save in single excel file as different sheet name and then convert that excel file in csv file .

The Agricultural Research Service of the US Department of Agriculture (USDA) in collaboration with other government agencies has a program to track changes in the sodium content of commercially processed and restaurant foods. This monitoring program includes these activities: Tracking sodium levels of ~125 popular foods, called "Sentinel Foods," by periodically sampling them at stores and restaurants around the country, followed by laboratory analyses. Tracking levels of "related" nutrients that could change when manufacturers reformulate their foods to reduce sodium; these related nutrients are potassium, total and saturated fat, total dietary fiber, and total sugar. Sharing the results of these monitoring activities to the public periodically in the Sodium Monitoring Dataset and USDA National Nutrient Database for Standard Reference and once every two years in the Food and Nutrient Database for Dietary Studies. The Sodium Monitoring Dataset is downloadable in Excel spreadsheet format. Resources in this dataset:Resource Title: Data Dictionary. File Name: SodiumMonitoringDataset_datadictionary.csvResource Description: Defines variables, descriptions, data types, character length, etc. for each of the spreadsheets in this Excel data file: Sentinel Foods - Baseline; Priority-2 Foods - Baseline; Sentinel Foods - Monitoring; Priority-2 Foods - Monitoring.Resource Title: Sodium Monitoring Dataset (MS Excel download). File Name: SodiumMonitoringDatasetUpdatedJuly2616.xlsxResource Description: Microsoft Excel : Sentinel Foods - Baseline; Priority-2 Foods - Baseline; Sentinel Foods - Monitoring; Priority Foods - Monitoring.

This is a Dataset Regarding the games available on the Nintendo Switch Console. The data is sorted on the Total Sales of the games The data was scrapped using Microsoft Excel from www.vgchartz.com .

Column Description: - Position: This represents the position of the game based on total sales. - Game: Name of the Game. - Publisher, Developer: The names of the Developer and Publisher. - VGChartz Score, Critic Score, User Score: Ratings for the games based on various parameters. - Total Shipped: Shows the total no.of units of the game shipped across the Globe. - Release Date: Gives the release Date for the game. - Last Update: Shows when the game was last updated.

The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the periods 2020-59 (centered in the year 2040) and 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical period.
An R script (create_boxplot.R) is provided which generates boxplots of change factors by NOAA Atlas 14 station, or for all NOAA Atlas 14 stations in a Florida HUC-8 basin or county. In addition, the R script basin_boxplot.R is provided as an example on how to create a wrapper function that will automate the generation of boxplots of change factors for all Florida HUC-8 basins. This Microsoft Word file (Documentation_R_script_create_boxplot.docx) serves as documentation on the code usage and available options for running the scripts. As described in the documentation, the R scripts rely on some of the Microsoft Excel spreadsheets published as part of this data release. The script uses basins defined in the "Florida Hydrologic Unit Code (HUC) Basins (areas)" from the Florida Department of Environmental Protection (FDEP; https://geodata.dep.state.fl.us/datasets/FDEP::florida-hydrologic-unit-code-huc-basins-areas/explore) and their names are listed in the file basins_list.txt provided with the script. County names are listed in the file counties_list.txt provided with the script. NOAA Atlas 14 stations located in each Florida HUC-8 basin or county are defined in the Microsoft Excel spreadsheet Datasets_station_information.xlsx which is part of this data release. Instructions are provided in code documentation (see highlighted text on page 7 of Documentation_R_script_create_boxplot.docx) so that users can modify the script to generate boxplots for basins different from the FDEP "Florida Hydrologic Unit Code (HUC) Basins (areas)."

In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed.

This data providers package provides the data collection configuration and supporting materials for reporting Chemical Contaminants in SSD1. These are to be used for the official data reporting phase.

The package includes:

The Standard Sample Description Version 2 XSD schema definition for CONTAMINANTS reporting.

The general and CONTAMINANTS SSD1 specific business rules applied for the automatic validation of the submitted datasets.

Excel Mapping tool to convert excel files after mapping into XML document.

Please follow the instructions below for the correct use of the mapping tool to avoid compromising its functionalities:

Download and save the MS Excel® Standard Sample Description file to your computer (do not open the file before saving and do not change the file name)

Download and save the file MS Excel® Simplified Reporting Format (do not open the file before saving)

Keep both Excel files in the same folder

Open both Excel files and enable the macros

Keep both files open in the same Excel instance when filling in the data

Guidance on how to run the validation report after submitting data to the DCF.

Business licenses issued by the Department of Business Affairs and Consumer Protection in the City of Chicago from 2002 to the present. This dataset contains a large number of records/rows of data and may not be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Notepad or Wordpad, to view and search.

Data fields requiring description are detailed below.

APPLICATION TYPE: ‘ISSUE’ is the record associated with the initial license application. ‘RENEW’ is a subsequent renewal record. All renewal records are created with a term start date and term expiration date. ‘C_LOC’ is a change of location record. It means the business moved. ‘C_CAPA’ is a change of capacity record. Only a few license types may file this type of application. ‘C_EXPA’ only applies to businesses that have liquor licenses. It means the business location expanded. 'C_SBA' is a change of business activity record. It means that a new business activity was added or an existing business activity was marked as expired.

LICENSE STATUS: ‘AAI’ means the license was issued. ‘AAC’ means the license was cancelled during its term. ‘REV’ means the license was revoked. 'REA' means the license revocation has been appealed.

LICENSE STATUS CHANGE DATE: This date corresponds to the date a license was cancelled (AAC), revoked (REV) or appealed (REA).

Business License Owner information may be accessed at: https://data.cityofchicago.org/dataset/Business-Owners/ezma-pppn. To identify the owner of a business, you will need the account number or legal name, which may be obtained from this Business Licenses dataset.

Data Owner: Business Affairs and Consumer Protection. Time Period: January 1, 2002 to present. Frequency: Data is updated daily.

This dataset contains all current and active business licenses issued by the Department of Business Affairs and Consumer Protection. This dataset contains a large number of records /rows of data and may not be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Notepad or Wordpad, to view and search.

Data fields requiring description are detailed below.

APPLICATION TYPE: 'ISSUE' is the record associated with the initial license application. 'RENEW' is a subsequent renewal record. All renewal records are created with a term start date and term expiration date. 'C_LOC' is a change of location record. It means the business moved. 'C_CAPA' is a change of capacity record. Only a few license types my file this type of application. 'C_EXPA' only applies to businesses that have liquor licenses. It means the business location expanded.

LICENSE STATUS: 'AAI' means the license was issued.

Business license owners may be accessed at: http://data.cityofchicago.org/Community-Economic-Development/Business-Owners/ezma-pppn To identify the owner of a business, you will need the account number or legal name.

Data Owner: Business Affairs and Consumer Protection

Time Period: Current

Frequency: Data is updated daily

This dataset contains all current and active business licenses issued by the Department of Business Affairs and Consumer Protection. This dataset contains a large number of records /rows of data and may not be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Notepad or Wordpad, to view and search.

Data fields requiring description are detailed below.

APPLICATION TYPE: 'ISSUE' is the record associated with the initial license application. 'RENEW' is a subsequent renewal record. All renewal records are created with a term start date and term expiration date. 'C_LOC' is a change of location record. It means the business moved. 'C_CAPA' is a change of capacity record. Only a few license types my file this type of application. 'C_EXPA' only applies to businesses that have liquor licenses. It means the business location expanded.

LICENSE STATUS: 'AAI' means the license was issued.

Business license owners may be accessed at: http://data.cityofchicago.org/Community-Economic-Development/Business-Owners/ezma-pppn To identify the owner of a business, you will need the account number or legal name.

Data Owner: Business Affairs and Consumer Protection

Time Period: Current

Frequency: Data is updated daily