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Data Loading and Data Exploration in python using pandas and matplotlib.

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In this video I have introduced to the different file formats that you may encounter while working with data in the beginning of you Data Science journey. I have also explained , how to load this dat files in the python using pandas.
You will also get to know how to explore the data that you have just Loaded in the pandas DataFrame.
Then I will show you how to plot data using matplotlib and seaborn libraries.
You will also get to know how to deal with NULL values your data using pandas.
Data Preparation and Analysis is the first step in the field of Data Science.
And If you are watching this video then you are way ahead of others.
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00:00 File formats that we are going to encounter
01:55 Data Loading using pandas library in python
02:55 Practical in jupyter notebook
04:47 Exploring Data using pandas, matplotlib and seaborn
10:33 Deal with NULL values
---------
Resources:
Join me here:
Please give a like❤😀 to the video if you like my demonstration and subscribe the channel. This is just for my motivation , nothing else.
Thanks for watching.
I am glad if I could be of any help to any one of you.
You can ask your doubts in the comments if you are have any.
✔ What are you going to learn ...........
- How to load data in python?
- How to load data using pandas.
- How to load ".data" and ".txt" files in pyhton?
- How to explore the data in python?
- What are different file formats that you may encounter?
- How to deal with NULL values ?
- How many NULL values are there in your data ?
- Clean data for Analysis and Machine learning.
- Pair plot using seaborn
- Plot using matplotlib.
- Separate independent and dependent variables.
#data_science
#How_to_load_data_python
#how_to_use_pandas_to_load_data
#data visualization #python matplotlib tutorial #data loading in python
#explore data
#plot using matplot #pairplot using seaborn
#file formats and seperator
#machine learning
#data analysis
#data preparation #data wrangling with python #dealing with null values in pandas
#dealing with null values in python
#load data in dataframe python
#data science learning
#start machine learning from scratch
#start data science from scratch
You will also get to know how to explore the data that you have just Loaded in the pandas DataFrame.
Then I will show you how to plot data using matplotlib and seaborn libraries.
You will also get to know how to deal with NULL values your data using pandas.
Data Preparation and Analysis is the first step in the field of Data Science.
And If you are watching this video then you are way ahead of others.
---------
00:00 File formats that we are going to encounter
01:55 Data Loading using pandas library in python
02:55 Practical in jupyter notebook
04:47 Exploring Data using pandas, matplotlib and seaborn
10:33 Deal with NULL values
---------
Resources:
Join me here:
Please give a like❤😀 to the video if you like my demonstration and subscribe the channel. This is just for my motivation , nothing else.
Thanks for watching.
I am glad if I could be of any help to any one of you.
You can ask your doubts in the comments if you are have any.
✔ What are you going to learn ...........
- How to load data in python?
- How to load data using pandas.
- How to load ".data" and ".txt" files in pyhton?
- How to explore the data in python?
- What are different file formats that you may encounter?
- How to deal with NULL values ?
- How many NULL values are there in your data ?
- Clean data for Analysis and Machine learning.
- Pair plot using seaborn
- Plot using matplotlib.
- Separate independent and dependent variables.
#data_science
#How_to_load_data_python
#how_to_use_pandas_to_load_data
#data visualization #python matplotlib tutorial #data loading in python
#explore data
#plot using matplot #pairplot using seaborn
#file formats and seperator
#machine learning
#data analysis
#data preparation #data wrangling with python #dealing with null values in pandas
#dealing with null values in python
#load data in dataframe python
#data science learning
#start machine learning from scratch
#start data science from scratch