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

Some Advanced Pandas functions are taught here.

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Amina Rasheed 4 months ago
in contrast, kindly any one here can guide type casting in Pandas
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Amina Rasheed 4 months ago
in contrast, kindly any one here can guide type casting in Pandas
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Omar Rashed 8 months ago
Assalamualikum sir. Assignment1: df = df.assign(height = pd.to_numeric(df['height'])) df.weight=df.weight.astype('int64') df.Favourite_Dish=df.Favourite_Dish.astype("category")
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Sheikh Irfan Ullah Khan 8 months ago
Asalam-0-Alaikum Dr Sab I have found these results after running the code of df.describe()height weights count 87.000000 87.000000 mean 5.547931 70.459770 std 0.333321 16.753899 min 5.000000 25.000000 25% 5.250000 60.000000 50% 5.600000 70.000000 75% 5.800000 80.000000 max 6.200000 125.000000These are different from your results. Is it right?
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Akhtar Alvi 7 months ago
Same here with df.describe(). Any solution
TAHA EHSAN ULLAH 9 months ago
After type casting: _____df.sort_values(by="weight")______________________________________height weight favourite_dish _____________________________________ 5.0 25 Biryani_______________________________________________________ 5.0 31 Biryani_______________________________________________________ 5.2 48 Biryani_______________________________________________________ 5.6 49 Chicken Pulao_______________________________________________ 5.0 50 Chicken Pulao
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TAHA EHSAN ULLAH 9 months ago
df.column() with paranthesis aik function ki trah deal krta hy jo k Atribute error deta hy jbky df.column dataframe mein individual columns ko access or onky upar kam krny k lye use hota hy
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TAHA EHSAN ULLAH 9 months ago
*Correction* its df.columns and it is used to show you the labels of all the columns in your table. It returns a list of the column names as text.
Sana Shah 9 months ago
sana your student
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Mohsin Muntazir 9 months ago
Type Casting is already done in previous video sir why you are asking for wrangling again ?
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