Course Content
Day-2: How to use VScode (an IDE) for Python?
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Day-3: Basics of Python Programming
This section will train you for Python programming language
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Day-4: Data Visualization and Jupyter Notebooks
You will learn basics of Data Visualization and jupyter notebooks in this section.
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Day-5: MarkDown language
You will learn whole MarkDown Language in this section.
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Day-10: Data Wrangling and Data Visualization
Data Wrangling and Visualization is an important part of Exploratory Data Analysis, and we are going to learn this.
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Day-11: Data Visualization in Python
We will learn about Data Visualization in Python in details.
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Day-12,13: Exploratory Data Analysis (EDA)
EDA stands for Exploratory Data Analysis. It refers to the initial investigation and analysis of data to understand the key properties and patterns within the dataset.
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Day-15: Data Wrangling Techniques (Beginner to Pro)
Data Wrangling in python
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Day-26: How to use Conda Environments?
We are going to learn conda environments and their use in this section
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Day-37: Time Series Analysis
In this Section we will learn doing Time Series Analysis in Python.
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Day-38: NLP (Natural Language Processing)
In this section we learn basics of NLP
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Day-39: git and github
We will learn about git and github
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Day-40: Prompt Engineering (ChatGPT for Social Media Handling)
Social media per activae rehna hi sab kuch hy, is main ap ko wohi training milay ge.
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Python ka Chilla for Data Science (40 Days of Python for Data Science)
About Lesson

Chalen kuch or plots bnatay hyn

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Ghayas uddin 6 months ago
where we have to send assignments?
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Aiman Mukhtar 6 months ago
for the correlation heat map this code is working: import seaborn as sns import matplotlib.pyplot as pltnumeric_columns = kashti.select_dtypes(include=['float64', 'int64']).columns corr_matrix = kashti[numeric_columns].corr()plt.figure(figsize=(10, 10)) sns.heatmap(corr_matrix, annot=True) plt.title('Correlation Heatmap') plt.show()
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Aiman Mukhtar 6 months ago
to plot in matplotlib.pyplot we use c import matplotlib.pyplot as pltplt.scatter(data=kashti, x="age", y="fare", c='pclass') plt.xlabel('Age') plt.ylabel('Fare') plt.title('Scatter Plot of Age vs Fare with Pclass') plt.show()
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Azeem Log 8 months ago
heat map not work
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Aiman Mukhtar 6 months ago
This will work probably: numeric_columns = kashti.select_dtypes(include=['float64', 'int64']).columns corr_matrix = kashti[numeric_columns].corr()plt.figure(figsize=(10, 10)) sns.heatmap(corr_matrix, annot=True) plt.title('Correlation Heatmap') plt.show()
Muhammad Haris Ahsan 8 months ago
@9:38 "color, colour, hue" nahi lgy ga Yahan "c" lgy ga only
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Shahid Aman 7 months ago
# Define a color palette (you can choose different colors) colors = {1: 'blue', 2: 'green', 3: 'red'}# Plot each group for pclass, group_data in kashti.groupby('pclass'): plt.scatter(group_data['age'], group_data['fare'], color=colors[pclass], label=f'Class {pclass}')# Add labels and legend plt.xlabel('Age') plt.ylabel('Fare') plt.legend(title='Passenger Class')
Ilyas Qasim 8 months ago
# Assignment: How to change the x and y axis titles with main title?boxchart = sns.boxplot(data=kashti, x="sex", y="fare", hue='pclass') boxchart.set_title('Assignment') boxchart.set_xlabel('Sex') boxchart.set_ylabel('Fare') boxchart
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Mamoon Abdullah 8 months ago
plt.scatter(data=kashti, x="age", y="fare", c=kashti["pclass"])
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komal Baloch 8 months ago
done
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Shadat Ali 9 months ago
Jio Murshid ji
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Siraj Shabbir 9 months ago
Data Visualization on iris and tips datasets : https://github.com/SirajAtFiverr/PKC-2023/blob/main/day_11/data_visualization.ipynb
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Muhammad Umar Farooq 9 months ago
Behtareen Siraj Bhai