MEAL officer learning log

Spent the whole day in the office. Changes in indicators were discussed and a priority action plan for obtaining missing data was determined. Prepared a draft report on the current progress of program implementation. Time spent: 8h

Today I continued work on the development of an add-in for Excel. The main task was to convert my Python transliteration function into a native vba script and further adapt it as a custom formula. Time spent: 4h

Today I started developing an add-in for Excel to speed up the processing of existing databases and reduce the number of errors due to the automation of checking the values ​​of some database fields. I defined the main logical blocks: checking the correctness of the entered data, interaction with the database of interviewed people and moving buttons of standard functions to improve access to them. Developed macros: quick conversion of formulas into values; correction and conversion of dates of birth; reproduction of lost dates of birth (if possible); checking the subordination of territorial units; Scheduled: Batch cleaning of data from garbage; Automatic determination of a person's gender by name (to supplement partial data); Highlighting the current row to simplify navigation on the sheet. Time spent: 8h

The Axes class in Matplotlib is a key component that represents an individual plot within a figure. It provides methods and attributes for customizing and manipulating various aspects of the plot, such as the axes limits, labels, ticks, grids, and more. To create an Axes object, you typically start by creating a Figure object using plt.figure(). Then, you can add one or more Axes objects to the figure using the add_subplot() or add_axes() methods. The add_subplot() method divides the figure into a grid of subplots, and add_axes() allows you to specify the position and size of the axes within the figure. Python code import matplotlib.pyplot as plt fig = plt.figure() ax = fig.add_subplot(1, 1, 1) The Axes object provides various methods and attributes to customize its properties. Some common properties you can modify include: Axes labels: Use set_xlabel() and set_ylabel() methods to set the x-axis and y-axis labels, respectively. Axes title: Use the set_title() method to set t...

Today I prepared the data for checking the beneficiaries against the Interpol database and checked them.

Matplotlib provides a wide range of plot types to visualize different types of data. Here are some of the commonly used plot types available in Matplotlib: Line Plot A line plot is a type of plot that displays the relationship between two continuous variables. It uses a series of data points connected by straight lines to show the trend or progression of the variables over a specified range or sequence. Line plots are commonly used to visualize time series data or to represent the change of a variable over different conditions or categories. Python code import matplotlib.pyplot as pyplot pyplot.plot([1,2,3,5,6], [1, 2, 3, 4, 6]) pyplot.axis([0, 7, 0, 10]) pyplot.show() Scatter Plot A scatter plot is a type of plot that shows the relationship between two continuous variables. It represents each data point as a point on the plot, with the x-axis representing one variable and the y-axis representing the other. Scatter plots are useful for identifying patterns, trends, or corr...

Step-by-step instruction for Clear button creation: Insert a blank button: Go to the "Insert" tab, click on "Buttons," and select a blank button. Customize the button: Adjust the formatting of the button to your preference. Add a bookmark action: Open the bookmarks panel and the selection panel on the view. Organize your slices into different categories. Create a bookmark: Double-click on the bookmark area, name it (e.g., "Reset Slices"), and configure the settings. Choose to capture only the data state and selected visuals. Clear all slices: Check if all slices are cleared. If not, select the slicer groups or individual slices that you want to clear, then update the bookmark. Link the bookmark to the button: Select the button, go to the "Action" tab, and choose the bookmark action you created (e.g., "Reset Slices"). Test the bookmark: Verify that the button clears all slices when clicked. Alternative method for clear all slices but...

Step-by-step instruction Open Power BI and navigate to the "Get Data" section. Click on "More options" and select the "Python" option. In the Python script editor, start by importing the pandas library as pd. This library will be used to handle the data. Create a variable called "my_data" and assign it the value of reading the Excel file using pandas. Specify the file location as "d:\Python tutorials\Power BI advanced dashboard advanced\dashboard advanced.xlsx". Use the pivot table function to summarize the data. Create a variable called "summary" and assign it the result of the pivot table operation. Set the index to the "city" column and use the "sum" aggregation function to calculate the sum of revenue and duration for each city. Use the "reset_index()" function to include the city names as part of the resulting table. Press "OK" to initiate the data processing. Explain that this...

Step-by-step instruction: To convert an existing line chart into a Python visual, you will utilize the matplotlib library. Select your visual and change its type to Python by selecting correspond button on the right panel. Begin by importing the necessary module with the following code: import matplotlib.pyplot as plt . Define the x-axis and y-axis variables for your chart. For the x-axis, you will use the "month name" column from your dataset. For the y-axis, you need to define three variables: y1 for the current year's profit, y2 for the previous year's profit, and y3 for the profit growth or decline. Make sure to accurately identify and assign the corresponding columns from your dataset to these variables. Proceed to define the plots for each y-axis variable using the plt.plot() function. You will create three separate plots, one for each variable. Begin with y1 by using plt.plot(x, y1) where x represents the x-axis values and y1 represents the y-axis ...