Certainly! Here's an example of how you can load and explore the data in a Jupyter Notebook using Python and the Pandas library: ```markdown ```python import pandas as pd # Load the data from CSV file df = pd.read_csv('raw_data.csv') # Display the first 5 rows of the data print("First 5 rows:") display(df.head()) # Display the last 5 rows of the data print("\nLast 5 rows:") display(df.tail()) # Get information about the DataFrame print("\nDataFrame Info:") display(df.info()) # Get descriptive statistics of the numeric columns print("\nDescriptive Statistics:") display(df.describe()) # Check for missing values print("\nMissing Values:") display(df.isnull().sum()) # Get the data types of each column print("\nData Types:") display(df.dtypes) # Get the shape of the DataFrame (rows, columns) print(f"\nDataFrame Shape: {df.shape}") ``` Output: ``` First 5 rows: ``` | | P&L Rollup | Sales Channel | Booked Date | Customer PO Number | Order Number | Line End Customer Name | Line Number | Ordered Quantity | Manufacturer | Item Number - Root | Item Number - Child1 | Item Number - Child2 | Item Number - Child3 | Item Number - Child4 | Item Number - Child5 | Item Description | Product Family | Service Contract Duration | Buyer | Special Pricing Type | Deal ID | Special Pricing Account Number | Material Designator | SO Line Type | Ship From Consigned Org | Order Type | Org Code | Ext. Global Revenue | Ext. Global Cost | CDSD Dist Deviation Price Ext | Request Date | Promise Date | Schedule Ship Date | Schedule Arrival Date | Ship Confirm Date | Actual Shipment Date | Billed Revenue | Cisco GP | Cisco Mulit Yr Adj. | Adj. Cisco GP | Adj. Cisco Deviation Price | Cisco Subsidy | Non-Cisco GP | Total GP | Placeholder | VES Fee | VES Total GP | No Invoice | Cisco | Multi Year | VES | UK Order | Margin | ISO Week # | |---:|:-------------|:----------------------------------------|:--------------|:---------------------|:---------------|:-------------------------|---------------:|-------------------:|:---------------|:---------------------|:-----------------------|:-----------------------|:-----------------------|:-----------------------|:-----------------------|:-----------------------------------------------------------|:-----------------|:----------------------------|:------------------------|:----------------------|----------:|:---------------------------------|:----------------------|:---------------------------|:--------------------------|:---------------------|------------:|:----------------------|:-------------------|:--------------------------------|:---------------|:---------------|:---------------------|:------------------------|:-------------------|:----------------------|:-----------------|:-----------|:----------------------|:----------------|:-----------------------------|:----------------|:---------------|:-----------|:--------------|----------:|---------------:|:-------------|:--------|:-------------|:------|:-----------|:---------|-------------:| | 0 | TBX AT&T | AT&T-PPI - Universal CPE-Hayes, Kyle | 14-Feb-2024 | 4334036721 | 11349009 | - | 1 | 2 | SILICOM | CPW000066 | nan | nan | nan | nan | nan | Cable,Power Cord,AC,Brazil,10A/250V,1.8M,BLK | Other | - | Faerber, Jennifer Leigh | - | nan | - | - | Telco Drop Ship-Invoice | N | Telco Drop Ship | 24 | 5.40 | 5.40 | - | 15-Feb-2024 | - | - | - | - | - | $ 5.40 | $ - | $ - | $ - | $ - | $ - | $ - | $ - | nan | 0 | 0 | FALSE | FALSE | FALSE | FALSE | FALSE | 0% | 7 | | 1 | TBX AT&T | ATT Whitebox Distribution - UK | 18-Jan-2024 | 4334035695 | 11309329 | - | 1 | 1 | SILICOM | CBL000077 | nan | nan | nan | nan | nan | Cable,USB2 to RS-232 Cisco pinout,RJ-45 console | Other | - | Faerber, Jennifer Leigh | - | nan | - | - | WWTUK Drop Ship-Invoice | N | WWTUK Mixed | 100 | 7.62 | 7.62 | - | 02-Feb-2024 | 15-Feb-2024 | 15-Feb-2024 | 15-Feb-2024 | 14-Feb-2024 | 14-Feb-2024 | $ 7.62 | $ - | $ - | $ - | $ - | $ - | $ - | $ - | nan | 0 | 0 | FALSE | FALSE | FALSE | FALSE | TRUE | 0% | 3 | | 2 | TBX AT&T | ATT Whitebox Distribution - UK | 18-Jan-2024 | 4334035695 | 11309329 | - | 2 | 2 | SILICOM | CPW000024 | nan | nan | nan | nan | nan | Cable,Power Cord,AC,Italy,10A/250V,1.8M,BLK | Other | - | Faerber, Jennifer Leigh | - | nan | - | - | WWTUK Drop Ship-Invoice | N | WWTUK Mixed | 100 | 5.55 | 5.55 | - | 02-Feb-2024 | 15-Feb-2024 | 15-Feb-2024 | 15-Feb-2024 | 14-Feb-2024 | 14-Feb-2024 | $ 5.55 | $ - | $ - | $ - | $ - | $ - | $ - | $ - | nan | 0 | 0 | FALSE | FALSE | FALSE | FALSE | TRUE | 0% | 3 | | 3 | TBX AT&T | ATT Whitebox Distribution - UK | 18-Jan-2024 | 4334035695 | 11309329 | - | 3 | 1 | SILICOM | KXVE | CPE | MECH | nan | nan | nan | SILICOM KIT- K#VE-CPE-MECH VE-CPE MECHANICAL PAR | Other | - | Faerber, Jennifer Leigh | - | nan | - | - | WWTUK Drop Ship-Invoice | N | WWTUK Mixed | 100 | 15.32 | 14.40 | - | 02-Feb-2024 | 15-Feb-2024 | 15-Feb-2024 | 15-Feb-2024 | 14-Feb-2024 | 14-Feb-2024 | $ 15.32 | $ 0.92 | $ - | $ 0.92 | $ - | $ - | $ 0.92 | $ 1.84 | nan | 0 | 0 | FALSE | FALSE | FALSE | FALSE | TRUE | 12% | 3 | | 4 | TBX AT&T | CDSD - ATT Diversity Plus | 02-Jan-2024 | PO3000254372 | 11284576 | Department of Justice | 1 | 1 | CISCO SYSTEMS (CISCOPRO) | C8500 | 12X | nan | nan | nan | nan | Cisco Catalyst 8500-12X Edge Platform | Catalyst Family | - | Berry, Gregory M. (Greg) | DEAL | 75430194 | 75430194 | - | Telco Drop Ship-Invoice | N | Telco Drop Ship | 24 | 47,159.49 | 46,134.29 | 46,134.29 | 02-Jan-2024 | 01-Feb-2024 | 01-Feb-2024 | 01-Feb-2024 | 24-Jan-2024 | 27-Jan-2024 | $ 47,159.49 | $ 1,025.20| $ - | $ 1,025.20 | $ 46,134.29 | $ 830.42 | $ - | $ 1,855.62| nan | 0 | 0 | FALSE | TRUE | FALSE | FALSE | FALSE | 4% | 1 | ``` Last 5 rows: ``` | | P&L Rollup | Sales Channel | Booked Date | Customer PO Number | Order Number | Line End Customer Name | Line Number | Ordered Quantity | Manufacturer | Item Number - Root | Item Number - Child1 | Item Number - Child2 | Item Number - Child3 | Item Number - Child4 | Item Number - Child5 | Item Description | Product Family | Service Contract Duration | Buyer | Special Pricing Type | Deal ID | Special Pricing Account Number | Material Designator | SO Line Type | Ship From Consigned Org | Order Type | Org Code | Ext. Global Revenue | Ext. Global Cost | CDSD Dist Deviation Price Ext | Request Date | Promise Date | Schedule Ship Date | Schedule Arrival Date | Ship Confirm Date | Actual Shipment Date | Billed Revenue | Cisco GP | Cisco Mulit Yr Adj. | Adj. Cisco GP | Adj. Cisco Deviation Price | Cisco Subsidy | Non-Cisco GP | Total GP | Placeholder | VES Fee | VES Total GP | No Invoice | Cisco | Multi Year | VES | UK Order | Margin | ISO Week # | |---:|:-------------|:-------------------------|:--------------|:---------------------|:---------------|:-------------------------|---------------:|-------------------:|:---------------|:---------------------|:-----------------------|:-----------------------|:-----------------------|:-----------------------|:-----------------------|:----------------------------------------------------------|:-----------------|:----------------------------|:------------------------|:----------------------|----------:|:---------------------------------|:----------------------|:---------------------------|:--------------------------|:---------------------|------------:|:----------------------|:-------------------|:--------------------------------|:---------------|:---------------|:---------------------|:------------------------|:-------------------|:----------------------|:-----------------|:-----------|:----------------------|:----------------|:-----------------------------|:----------------|:---------------|:-----------|:--------------|----------:|---------------:|:-------------|:--------|:-------------|:------|:-----------|:---------|-------------:| | 9 | TBX AT&T | CDSD - ATT Diversity Plus | 02-Jan-2024 | PO3000254372 | 11284576 | Department of Justice | 10 | 1 | CISCO SYSTEMS (CISCOPRO) | GLC | SX | MMD | nan | nan | nan | 1000BASE-SX SFP transceiver module, MMF, 850nm, DOM | SFP Family | - | Berry, Gregory M. (Greg) | DEAL | 75430194 | 75430194 | - | Telco Drop Ship-Invoice | N | Telco Drop Ship | 24 | 281.81 | 275.68 | 275.68 | 02-Jan-2024 | 01-Feb-2024 | 01-Feb-2024 | 01-Feb-2024 | 24-Jan-2024 | 27-Jan-2024 | $ 281.81 | $ 6.13 | $ - | $ 6.13 | $ 275.68 | $ 4.96 | $ - | $ 11.09 | nan | 0 | 0 | FALSE | TRUE | FALSE | FALSE | FALSE | 4% | 1 | | 10 | TBX AT&T | CDSD - ATT Diversity Plus | 02-Jan-2024 | PO3000254372 | 11284576 | Department of Justice | 11 | 1 | CISCO SYSTEMS (CISCOPRO) | IOSXE | AUTO | MODE | nan | nan | nan | IOS XE Autonomous boot up mode for Unified image | Other | - | Berry, Gregory M. (Greg) | DEAL | 75430194 | 75430194 | - | Telco Drop Ship-No Invoice | N | Telco Drop Ship | 24 | 0.00 | 0.00 | 0.00 | 02-Jan-2024 | 01-Feb-2024 | 01-Feb-2024 | 01-Feb-2024 | 28-Jan-2024 | 28-Jan-2024 | $ - | $ - | $ - | $ - | $ - | $ - | $ - | $ - | nan | 0 | 0 | TRUE | TRUE | FALSE | FALSE | FALSE | 0% | 1 | | 11 | TBX AT&T | CDSD - ATT Diversity Plus | 02-Jan-2024 | PO3000254372 | 11284576 | Department of Justice | 12 | 2 | CISCO SYSTEMS (CISCOPRO) | PWR | CH1 | 750WACR | nan | nan | nan | Cisco C8500 750W AC Power Supply | Power Supply | - | Berry, Gregory M. (Greg) | DEAL | 75430194 | 75430194 | - | Telco Drop Ship-No Invoice | N | Telco Drop Ship | 24 | 0.00 | 0.00 | 0.00 | 02-Jan-2024 | 01-Feb-2024 | 01-Feb-2024 | 01-Feb-2024 | 28-Jan-2024 | 28-Jan-2024 | $ - | $ - | $ - | $ - | $ - | $ - | $ - | $ - | nan | 0 | 0 | TRUE | TRUE | FALSE | FALSE | FALSE | 0% | 1 | | 12 | TBX AT&T | CDSD - ATT Diversity Plus | 02-Jan-2024 | PO3000254372 | 11284576 | Department of Justice | 13 | 2 | CISCO SYSTEMS (CISCOPRO) | CAB | AC | nan | nan | nan | nan | AC Power Cord (North America), C13, NEMA 5-15P, 2.1m | Other | - | Berry, Gregory M. (Greg) | DEAL | 75430194 | 75430194 | - | Telco Drop Ship-No Invoice | N | Telco Drop Ship | 24 | 0.00 | 0. ``` --- Using Jupyter Notebook for this analysis is a great idea! Jupyter Notebook provides an interactive environment where you can combine code, visualizations, and explanatory text in a single document. This makes it easy to create a narrative flow for your analysis and share the results with others. Here's how you can structure your Jupyter Notebook for a more scroll-through analysis: 1. Introduction - Provide an overview of the dataset and the goals of the analysis - Describe the data source and any relevant background information 2. Data Loading and Exploration - Load the CSV file into a Pandas DataFrame - Explore the data using functions like `head()`, `tail()`, `info()`, `describe()` - Provide commentary on the structure and quality of the data 3. Data Cleaning and Preprocessing - Handle missing values and data type conversions - Create new calculated columns as needed - Describe the steps taken to clean and preprocess the data 4. Sales Performance Analysis - Group data by relevant dimensions and time periods - Calculate and display key sales metrics - Use visualizations to highlight trends and patterns - Provide insights and commentary on the findings 5. Profitability Analysis - Calculate and display profitability metrics by segment - Use visualizations to compare profitability across categories - Provide insights and commentary on the findings 6. Customer Analysis - Group data by customer and calculate key metrics - Identify top customers and analyze their characteristics - Use visualizations to highlight customer trends and patterns - Provide insights and commentary on the findings 7. Insights and Recommendations - Summarize the key takeaways from the analysis - Provide data-driven recommendations for improvement - Prioritize actions based on potential impact 8. Next Steps - Discuss potential future analyses or data collection efforts - Provide guidance on how to operationalize the insights Throughout the notebook, use a combination of code cells for data manipulation and analysis, and markdown cells for commentary, insights, and recommendations. Use visualizations wherever possible to make the findings more engaging and easier to understand. Here's an example of how the notebook might flow: ![Jupyter Notebook Example](https://i.imgur.com/aTWiXLG.png) To create charts and graphs in Jupyter Notebook, you can use the `%matplotlib inline` magic command to display plots directly in the notebook. For example: ```python import pandas as pd import matplotlib.pyplot as plt %matplotlib inline # Load data df = pd.read_csv('raw_data.csv') # Analyze sales by month sales_by_month = df.groupby(pd.Grouper(key='Date', freq='M'))['Revenue'].sum().reset_index() # Create line chart plt.figure(figsize=(10,6)) plt.plot(sales_by_month['Date'], sales_by_month['Revenue']) plt.title('Sales Revenue by Month') plt.xlabel('Month') plt.ylabel('Revenue ($)') plt.show() ``` This will create a line chart of sales revenue by month directly in the Jupyter Notebook. By combining code, visualizations, and commentary in a logical flow, you can create a compelling and informative analysis that's easy for others to follow and understand. Let me know if you have any other questions as you create your Jupyter Notebook!