Библиотека дата-сайентиста | Data Science, Machine learning, анализ данных, машинное обучение

📊 Промпт для генерации визуализаций данных

Используйте этот промпт для построения графиков с помощью Matplotlib.

🔹 Промпт:

I want you to act as a data scientist coding in Python. Given a dataframe {dataframe name} containing the columns {column names}, use Matplotlib to plot a {chart type} that shows the relationship between {variables}. Additionally, annotate the plot with the following details: {annotation requirements}. Format the plot by adjusting {specific formatting preferences}. Finally, change the plot's theme to {theme} to match the visual style of {theme description}.

Результат:
🔹 Качественные и профессиональные визуализации данных.
🔹 Подробное оформление и аннотации на графиках.
🔹 Удобное и понятное оформление графиков с использованием популярных тем.

✔️ Пример:

Исходный датафрейм с данными о возрасте, доходе и уровне образования:

import pandas as pd

data = {
    'age': [25, 30, 35, 40, 45],
    'income': [50000, 60000, 70000, 80000, 90000],
    'education_level': ['Bachelors', 'Masters', 'PhD', 'Bachelors', 'Masters']
}

df = pd.DataFrame(data)

💬 Пример использования промпта:

I want you to act as a data scientist coding in Python. Given a dataframe df containing the columns ['age', 'income', 'education_level'], use Matplotlib to plot a scatter plot that shows the relationship between age and income. Additionally, annotate the plot with the following details: highlight the highest and lowest income values. Format the plot by adjusting the title, axis labels, and grid lines. Finally, change the plot's theme to seaborn-darkgrid to match the visual style of a clean and modern plot with dark gridlines.

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2.15K viewsedited  Mar 20 at 07:03

📊 Промпт для генерации визуализаций данных

Используйте этот промпт для построения графиков с помощью Matplotlib.

🔹 Промпт:

I want you to act as a data scientist coding in Python. Given a dataframe {dataframe name} containing the columns {column names}, use Matplotlib to plot a {chart type} that shows the relationship between {variables}. Additionally, annotate the plot with the following details: {annotation requirements}. Format the plot by adjusting {specific formatting preferences}. Finally, change the plot's theme to {theme} to match the visual style of {theme description}.

import pandas as pd

data = {
    'age': [25, 30, 35, 40, 45],
    'income': [50000, 60000, 70000, 80000, 90000],
    'education_level': ['Bachelors', 'Masters', 'PhD', 'Bachelors', 'Masters']
}

df = pd.DataFrame(data)

I want you to act as a data scientist coding in Python. Given a dataframe df containing the columns ['age', 'income', 'education_level'], use Matplotlib to plot a scatter plot that shows the relationship between age and income. Additionally, annotate the plot with the following details: highlight the highest and lowest income values. Format the plot by adjusting the title, axis labels, and grid lines. Finally, change the plot's theme to seaborn-darkgrid to match the visual style of a clean and modern plot with dark gridlines.