diff --git a/.idea/.name b/.idea/.name
deleted file mode 100644
index ce5cb5f4..00000000
--- a/.idea/.name
+++ /dev/null
@@ -1 +0,0 @@
-py
\ No newline at end of file
diff --git a/.idea/encodings.xml b/.idea/encodings.xml
deleted file mode 100644
index 97626ba4..00000000
--- a/.idea/encodings.xml
+++ /dev/null
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\ No newline at end of file
diff --git a/.idea/misc.xml b/.idea/misc.xml
deleted file mode 100644
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+++ /dev/null
@@ -1,14 +0,0 @@
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\ No newline at end of file
diff --git a/.idea/modules.xml b/.idea/modules.xml
deleted file mode 100644
index 3a654885..00000000
--- a/.idea/modules.xml
+++ /dev/null
@@ -1,8 +0,0 @@
-
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\ No newline at end of file
diff --git a/.idea/py.iml b/.idea/py.iml
deleted file mode 100644
index 13eccfad..00000000
--- a/.idea/py.iml
+++ /dev/null
@@ -1,11 +0,0 @@
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diff --git a/.idea/vcs.xml b/.idea/vcs.xml
deleted file mode 100644
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--- a/.idea/vcs.xml
+++ /dev/null
@@ -1,6 +0,0 @@
-
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\ No newline at end of file
diff --git a/Basics/Exercise/25_decorators/25_decorators.md b/Basics/Exercise/25_decorators/25_decorators.md
index 995bee68..3e7ab915 100644
--- a/Basics/Exercise/25_decorators/25_decorators.md
+++ b/Basics/Exercise/25_decorators/25_decorators.md
@@ -10,7 +10,7 @@ example:
factorial(1.354) : raise Exception or print error message
factorial(-1) : raise Exception or print error message
- factorial(5) : 60
+ factorial(5) : 120
```
[Solution](https://github.com/codebasics/py/blob/master/Basics/Exercise/25_decorators/25_decorators.py)
diff --git a/DataScience/CelebrityFaceRecognition/images_dataset/serena_williams/uUa6x3eXf3__zFaIfjkC0QysTGUwuhWOWoYEAUTunGv70HZ-UXA62U0sGCPucHm4pqxqPQWinZiXVNLmZFcZ6RF9aL8cZ5_kZGD0kziwbD16kWk1WWK5e39OyAPwaHjIzGqtAshq-1920x1080.png b/DataScience/CelebrityFaceRecognition/images_dataset/serena_williams/uUa6x3eXf3__zFaIfjkC0QysTGUwuhWOWoYEAUTunGv70HZ-UXA62U0sGCPucHm4pqxqPQWinZiXVNLmZFcZ6RF9aL8cZ5_kZGD0kziwbD16kWk1WWK5e39OyAPwaHjIzGqtAshq-1920x1080.png
deleted file mode 100644
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diff --git a/TechTopics/DataScienceRoadMap2020/data_science_roadmap_2020.md b/TechTopics/DataScienceRoadMap2020/data_science_roadmap_2020.md
index 8df94aba..8086a1b1 100644
--- a/TechTopics/DataScienceRoadMap2020/data_science_roadmap_2020.md
+++ b/TechTopics/DataScienceRoadMap2020/data_science_roadmap_2020.md
@@ -1,94 +1,94 @@
-## Learn data science step by step in 6 months
-----------------------------------------------
-
-Following is a schedule to learn data science step by step considering **4 hours** of dedicated, focused study every single day. This program is perfect for beginners with no knowledge of data science and programming.
-
-### Week 1 and 2: Excel and Statistics
-
-* Excel
- - Google templates gallery for personal finance etc : https://docs.google.com/spreadsheets/u/0/?ftv=1
- - Budget planner: https://www.vertex42.com/ExcelTemplates/budgets.html
- - Chandoo's youtube channel: https://www.youtube.com/channel/UC8uU_wruBMHeeRma49dtZKA
- - Chandoo's website: https://chandoo.org/
-
-* Statistics
- - Khan academy: https://www.khanacademy.org/math/statistics-probability
- - Khan academy youtube: https://www.youtube.com/playlist?list=PL1328115D3D8A2566
- - Statistics by Marin : https://www.youtube.com/playlist?list=PLqzoL9-eJTNBZDG8jaNuhap1C9q6VHyVa
- - Statquest youtube channel: https://www.youtube.com/user/joshstarmer
-
-### Week 3 and 4: Python
-
-* Python
- - My Python course that is 5X better than the free playlists: https://codebasics.io/courses/python-for-beginner-and-intermediate-learners
- - Codebasics python tutorials (first 16) - https://www.youtube.com/playlist?list=PLeo1K3hjS3uv5U-Lmlnucd7gqF-3ehIh0
- - Codebasics python HINDI tutorials (first 16)- https://www.youtube.com/playlist?list=PLPbgcxheSpE1DJKfdko58_AIZRIT0TjpO
- - Make sure to work on exercises
-* R
- - Marin's lectures: https://www.youtube.com/playlist?list=PLqzoL9-eJTNBlVXxWvJkq0dtVut2sICUW
-
-### Week 5, 6, 7, 8: Numpy, Pandas, Data Visualization Libraries
-
-* NumPy and Pandas
- - Codebasics Numpy playlist: https://www.youtube.com/playlist?list=PLeo1K3hjS3uset9zIVzJWqplaWBiacTEU
- - Codebasics pandas playlist (first 9): https://www.youtube.com/playlist?list=PLeo1K3hjS3uuASpe-1LjfG5f14Bnozjwy
-
-* Visualization library
- - Matplotlib: codebasics matplotlib playlist: https://www.youtube.com/playlist?list=PLeo1K3hjS3uu4Lr8_kro2AqaO6CFYgKOl
- - Seaborn: codebasics seaborn tutorials: https://www.youtube.com/playlist?list=PLJIOr9Je9wzHT-ptgfelpt2Nyx4VGX_j9
-
-* Kaggle exploratory data analysis
- - Notebooks: https://www.kaggle.com/notebooks
- - Datasets: https://www.kaggle.com/datasets
-
-### Week 9, 10, 11, 12: Machine Learning
-
-* Machine learning
- - codebasics ml playlist (first 16): https://www.youtube.com/playlist?list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw
- - data science regression project: same playlist as above. Tutorial 18 to 25
- - HINDI codebasics ml playlist (first 14): https://www.youtube.com/playlist?list=PLPbgcxheSpE0aBsefANDYe2X_-tyJbBMr
-
-### Week 13, 14, 15, 16: Deep Learning
-
-* Deep learning (artificial neural network, convolutional neural network, recurrent neural network)
- - codebasics deep learning playlist: https://www.youtube.com/playlist?list=PLeo1K3hjS3uu7CxAacxVndI4bE_o3BDtO
-
-### Week 17, 18, 19, 20: SQL & MongoDB
-
-* SQL
- - My SQL course for data professionals, if you do this you don't have to look at any other resources: https://codebasics.io/courses/sql-beginner-to-advanced-for-data-professionals
- - kudavenkat playlist (first 16): https://www.youtube.com/playlist?list=PL08903FB7ACA1C2FB
- - khanacademy SQL course: https://www.khanacademy.org/computing/computer-programming/sql
-
-* MongoDB
- - https://www.coursera.org/learn/introduction-mongodb
-
-### Week 21, 22, 23, 24: BI tools
-
-If you don't have a strong reason to choose between Power BI and Tableau, I would suggest choosing Power BI as it is increasing becoming popular. Microsoft is investing a lot in this tool and accordingly to Gartner's magic quadrant, Power BI is leading the data analytics market as of 2022.
-
-* Power BI (project)
- - My Power BI course that can make you job ready: https://codebasics.io/courses/power-bi-data-analysis-with-end-to-end-project
- - codebasics sales insights project: https://www.youtube.com/playlist?list=PLeo1K3hjS3uva8pk1FI3iK9kCOKQdz1I9
- - personal finance management project: https://www.youtube.com/watch?v=pqSoCa2NGj4
-
-* Tableau
- - Codebasics sales insights project: https://www.youtube.com/playlist?list=PLeo1K3hjS3usDI9XeUgjNZs6VnE0meBrL
- - HINDI codebasics sales insights project: https://www.youtube.com/playlist?list=PLPbgcxheSpE2B7YFfOualUTlRhgnQR7Kn
- - Abhishek Agarwal: https://www.youtube.com/playlist?list=PL6_D9USWkG1C4raCOTlTf_oq4XnNNNtm9
- - Bharti consultancy: https://www.youtube.com/playlist?list=PLyD1XCIRA3gQmN73dHwQWr4R08ABZFMtZ
-
-
-## Soft skills
----------------
-* Learn anything effectively: https://www.youtube.com/watch?v=yZFrSDjRvjk
-
-* Group learning
- - Codebasics discord server: https://discord.gg/r42Kbuk
- - Hold each other accountable
-
-## Books and other resources
---------------------------------------
-* Free book on statistics: http://greenteapress.com/thinkstats/thinkstats.pdf
-* Another good book on statistics (not free) Naked Statistics - Charles Wheelan
-
+## Learn data science step by step in 6 months
+----------------------------------------------
+
+Following is a schedule to learn data science step by step considering **4 hours** of dedicated, focused study every single day. This program is perfect for beginners with no knowledge of data science and programming.
+
+### Week 1 and 2: Excel and Statistics
+
+* Excel
+ - Google templates gallery for personal finance etc : https://docs.google.com/spreadsheets/u/0/?ftv=1
+ - Budget planner: https://www.vertex42.com/ExcelTemplates/budgets.html
+ - Chandoo's youtube channel: https://www.youtube.com/channel/UC8uU_wruBMHeeRma49dtZKA
+ - Chandoo's website: https://chandoo.org/
+
+* Statistics
+ - Khan academy: https://www.khanacademy.org/math/statistics-probability
+ - Khan academy youtube: https://www.youtube.com/playlist?list=PL1328115D3D8A2566
+ - Statistics by Marin : https://www.youtube.com/playlist?list=PLqzoL9-eJTNBZDG8jaNuhap1C9q6VHyVa
+ - Statquest youtube channel: https://www.youtube.com/user/joshstarmer
+
+### Week 3 and 4: Python
+
+* Python
+ - My Python course that is 5X better than the free playlists: https://codebasics.io/courses/python-for-beginner-and-intermediate-learners
+ - Codebasics python tutorials (first 16) - https://www.youtube.com/playlist?list=PLeo1K3hjS3uv5U-Lmlnucd7gqF-3ehIh0
+ - Codebasics python HINDI tutorials (first 16)- https://www.youtube.com/playlist?list=PLPbgcxheSpE1DJKfdko58_AIZRIT0TjpO
+ - Make sure to work on exercises
+* R
+ - Marin's lectures: https://www.youtube.com/playlist?list=PLqzoL9-eJTNBlVXxWvJkq0dtVut2sICUW
+
+### Week 5, 6, 7, 8: Numpy, Pandas, Data Visualization Libraries
+
+* NumPy and Pandas
+ - Codebasics Numpy playlist: https://www.youtube.com/playlist?list=PLeo1K3hjS3uset9zIVzJWqplaWBiacTEU
+ - Codebasics pandas playlist (first 9): https://www.youtube.com/playlist?list=PLeo1K3hjS3uuASpe-1LjfG5f14Bnozjwy
+
+* Visualization library
+ - Matplotlib: codebasics matplotlib playlist: https://www.youtube.com/playlist?list=PLeo1K3hjS3uu4Lr8_kro2AqaO6CFYgKOl
+ - Seaborn: codebasics seaborn tutorials: https://www.youtube.com/playlist?list=PLJIOr9Je9wzHT-ptgfelpt2Nyx4VGX_j9
+
+* Kaggle exploratory data analysis
+ - Notebooks: https://www.kaggle.com/notebooks
+ - Datasets: https://www.kaggle.com/datasets
+
+### Week 9, 10, 11, 12: Machine Learning
+
+* Machine learning
+ - codebasics ml playlist (first 16): https://www.youtube.com/playlist?list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw
+ - data science regression project: same playlist as above. Tutorial 18 to 25
+ - HINDI codebasics ml playlist (first 14): https://www.youtube.com/playlist?list=PLPbgcxheSpE0aBsefANDYe2X_-tyJbBMr
+
+### Week 13, 14, 15, 16: Deep Learning
+
+* Deep learning (artificial neural network, convolutional neural network, recurrent neural network)
+ - codebasics deep learning playlist: https://www.youtube.com/playlist?list=PLeo1K3hjS3uu7CxAacxVndI4bE_o3BDtO
+
+### Week 17, 18, 19, 20: SQL & MongoDB
+
+* SQL
+ - My SQL course for data professionals, if you do this you don't have to look at any other resources: https://codebasics.io/courses/sql-beginner-to-advanced-for-data-professionals
+ - kudavenkat playlist (first 16): https://www.youtube.com/playlist?list=PL08903FB7ACA1C2FB
+ - khanacademy SQL course: https://www.khanacademy.org/computing/computer-programming/sql
+
+* MongoDB
+ - https://www.coursera.org/learn/introduction-mongodb
+
+### Week 21, 22, 23, 24: BI tools
+
+If you don't have a strong reason to choose between Power BI and Tableau, I would suggest choosing Power BI as it is increasing becoming popular. Microsoft is investing a lot in this tool and accordingly to Gartner's magic quadrant, Power BI is leading the data analytics market as of 2022.
+
+* Power BI (project)
+ - My Power BI course that can make you job ready: https://codebasics.io/courses/power-bi-data-analysis-with-end-to-end-project
+ - codebasics sales insights project: https://www.youtube.com/playlist?list=PLeo1K3hjS3uva8pk1FI3iK9kCOKQdz1I9
+ - personal finance management project: https://www.youtube.com/watch?v=pqSoCa2NGj4
+
+* Tableau
+ - Codebasics sales insights project: https://www.youtube.com/playlist?list=PLeo1K3hjS3usDI9XeUgjNZs6VnE0meBrL
+ - HINDI codebasics sales insights project: https://www.youtube.com/playlist?list=PLPbgcxheSpE2B7YFfOualUTlRhgnQR7Kn
+ - Abhishek Agarwal: https://www.youtube.com/playlist?list=PL6_D9USWkG1C4raCOTlTf_oq4XnNNNtm9
+ - Bharti consultancy: https://www.youtube.com/playlist?list=PLyD1XCIRA3gQmN73dHwQWr4R08ABZFMtZ
+
+
+## Soft skills
+---------------
+* Learn anything effectively: https://www.youtube.com/watch?v=yZFrSDjRvjk
+
+* Group learning
+ - Codebasics discord server: https://discord.gg/r42Kbuk
+ - Hold each other accountable
+
+## Books and other resources
+--------------------------------------
+* Free book on statistics: http://greenteapress.com/thinkstats/thinkstats.pdf
+* Another good book on statistics (not free) Naked Statistics - Charles Wheelan
+
diff --git a/pandas/2_dataframe_basics/weather_data.csv b/pandas/2_dataframe_basics/weather_data.csv
index e77119aa..025e1f00 100644
--- a/pandas/2_dataframe_basics/weather_data.csv
+++ b/pandas/2_dataframe_basics/weather_data.csv
@@ -1,7 +1,7 @@
-day,temperature,windspeed,event
-1/1/2017,32,6,Rain
-1/2/2017,35,7,Sunny
-1/3/2017,28,2,Snow
-1/4/2017,24,7,Snow
-1/5/2017,32,4,Rain
-1/6/2017,31,2,Sunny
+day,temperature,windspeed,event
+1/1/2017,32,6,Rain
+1/2/2017,35,7,Sunny
+1/3/2017,28,2,Snow
+1/4/2017,24,7,Snow
+1/5/2017,32,4,Rain
+1/6/2017,31,2,Sunny
diff --git a/pandas/3_different_ways_of_creating_dataframe/weather_data.csv b/pandas/3_different_ways_of_creating_dataframe/weather_data.csv
index 56914a22..90fefa18 100644
--- a/pandas/3_different_ways_of_creating_dataframe/weather_data.csv
+++ b/pandas/3_different_ways_of_creating_dataframe/weather_data.csv
@@ -1,4 +1,4 @@
-day,temperature,windspeed,event
-1/1/2017,32,6,Rain
-1/2/2017,35,7,Sunny
-1/3/2017,28,2,Snow
+day,temperature,windspeed,event
+1/1/2017,32,6,Rain
+1/2/2017,35,7,Sunny
+1/3/2017,28,2,Snow