WHAT A TRAINER, HATS OFF TO THIS LADY, EVEN THOUGH I DIDN'T MISS THE SINGLE CONTENT AND FOR 5-7 HRS I CONTINUOUSLY SAT AND WATCHED THE VIDEO AND PARALLELLY PRACTICED THE SAME. I REALLY LIKED THE VIDEO, YOU MADE MY ALL CONCEPTS CLEAR IN A SINGLE VIDEO AND MADE MY LIFE EASY TOO. THANK YOU SO MUCH
Thanks to Uma and KSR Datavizon for this very informative session... I watched this session at the right time of my journey... I am very thankful to you guys... The way she explained every topic and how she was interacting was very impressive... Best session on Power BI i ever watched... 👏👏👏👏
I had made this full project after seeing your video and I would like to thank you soo much that you made us understand the topics in a very easy way.. Thank you for all your efforts...👌👌👌
Thanks a tonn. I have been searching for such video for long time. Thanks a million for making this. This is so informative and helpful. Cleared all my doubts. 🙏
25:15 mark table as date- very important step and helped me gain my answer regarding my Query with date. Also if we try to implement same concept with different date columns, it won't be validated, because it consist of duplicate date values and not distinct once, hence this is also an additional reason for we to consider creating master_date_table as an independent dimension table.
Wow amazing session the way uma explaining concepts is flawless enjoyed the complete session. Looking forward to more interactive sessions like this. Thank You 🤩👍
Truly Insightful session, engaging and Instructor explaining the concepts in the simplest manner possible, very supportive and humble. Hats Off to you :). Also Thanks for making the premium content available for free.
Thanks for content like this, your project helped me to understand end to end approach of how power bi works. please add more videos. your work is really appreciatable.
Let me begin by saying this first, The video is amazing. Quick suggestion for calculating the number of active customers: The following DAX formula feels to me like a better fit. Given that it is the same table that we use for our purposes and is easy to read. = CALCULATE(count(Bank_Churn[CustomerId]),Bank_Churn[IsActiveMember] = 1) Similarly for the inactive members it can be easy to read as follows: = CALCULATE(COUNT(Bank_Churn[CustomerId]),Bank_Churn[IsActiveMember] = 0) Thank you for the amazing videos.
Thanks a tonnnn. I have been searching for such video for long time. Thanks a million for making this. This is so informative and helpful. Cleared all my doubts. 🙏🙏🙏🙏🙏
Good explain i could understand with uma mam brief lecture on project Mam i request you do more complete projects in different kinds of scenarios please...You have excellent teach skills nice english communication..
Hi hope you are doing well This video helps us a lot and the way you explained is very detailed, and you are providing keen knowledge about Power Bi Thank you
Amazing explanation from the ksr team, Request you to make end to end project video on supply chain solutions (sales, CRM, procurement, finance, marketing, operations)
Hello mam, can u upload one more new project bacuse its very helpful to us. I trid this project its very easy to learn nice and nice. Requested to you pls uplaod another new topic project
@@KSRDatavizon ok thnks. I m doing internship now but we hv don't know abt projexlct and i saw your videos and i hav done your project bank domain so pls giv us one more project pls
Hi , thanks for giving this most valuable information this cleared some of doubts, i have question that when you created new table as calculation how its automatic connect with fact table?
I have question that datemaster table values are being used for analysis exit of customer, "DOJ+Tenure",should be used for churn analysis.....but DateOfJoining has been used ???
Hi maam your explanation is good and i have to request you please increase when you write dax formula the screen is not visible so word not correct find out that
hello i am unable to do the dax calculations can someone please help me with it i am getting an error saying that we cannot do the dax calculations if the data type is different but i made sure that both are in integers Please reply here if anyone is familiar with this query
Troubleshooting Line Chart Sorting Issues Understanding the Problem: It seems that your line chart is interpreting the month names as text values, rather than dates, which is causing the sorting to be alphabetical instead of chronological. Potential Solutions: Ensure Correct Data Type: Check the Column Properties: Right-click on the month column in your data source and verify that its data type is set to "Date" or a similar format. If it's set as "Text", change it to the appropriate date format. Create a Date Table: If your month data is not in a date format, consider creating a separate date table with columns like "Year", "Month", and "MonthName". This can provide a cleaner and more efficient way to handle dates in your visualizations. Sort Axis Manually: Right-click on the Axis: In your line chart, right-click on the axis that contains the month names. Select "Sort Axis": Choose the appropriate sorting option (e.g., "Sort Ascending" or "Sort Descending") based on your desired order. Use a Calculated Column: Create a Calculated Column: If you need more complex sorting logic, create a calculated column that assigns a numerical value to each month (e.g., 1 for January, 2 for February, etc.). Sort by Calculated Column: Use this calculated column as the axis in your line chart to ensure proper sorting. Example (Power BI): If you're using Power BI, you could create a calculated column to assign a numerical value to each month: Code snippet MonthNumber = MONTH('YourTableName'[Month]) Use code with caution. Then, use this "MonthNumber" column on the axis of your line chart. Additional Tips: Check for Formatting Issues: Ensure that your month names are formatted consistently (e.g., "January" vs. "Jan"). Inconsistent formatting can affect sorting. Consider Regional Settings: If you're working with different regional settings, make sure that the month names are recognized correctly in your data source. By following these steps and addressing the potential causes, you should be able to resolve the sorting issue in your line chart and ensure that the months are displayed in the correct order. Please provide more details about your data source and visualization tool if you need further assistance.
Thank you madam...Very very good video...I can't find right end to end report with healthcare data or hospital data .Please upload one video with healthcare data analysis ...Thank you
I appreciate your kind words about the video. I'm glad you found it helpful. I'm always looking for opportunities to create more videos on different topics, including healthcare data analysis. While I don't currently have a specific video dedicated to end-to-end analysis with healthcare data, I can provide some resources that may be helpful: th-cam.com/video/ahQrhyKmxGI/w-d-xo.htmlsi=9gTVCxaV0aU1FKEV
Its a good video, but if you would have included the Data refresh after RLS , issues y it doesn't work in desktop and powerbi service it would be great... Errors and issues also has to be explained.. It will be helpful
I’m so glad to hear that this video met your needs! 😊 If you enjoyed it, please consider subscribing to our channel for more content like this. And if there’s anything specific you’d like to see in the future, feel free to let me know. Thanks for watching!
When you are dealing with a date column stored as text and get errors when converting it to a proper date format, it usually indicates inconsistencies or unexpected formats in the data. Here’s how you can approach this issue: 1. Inspect the Data Format: First, check if there are any anomalies in the date format such as: Mixed formats (e.g., DD/MM/YYYY vs. MM/DD/YYYY) Missing or invalid dates (e.g., "NULL", "NaN", or empty strings) Incorrect characters or symbols You can inspect the unique date formats using the following code (assuming you're using Python and pandas): python Copy code df['date_column'].unique() 2. Handle Missing or Invalid Dates: You need to either clean or remove the rows with missing or invalid dates. You can replace them with a default value, such as NaT (Not a Time), or you can drop them entirely. python Copy code df['date_column'].replace(['NULL', 'NaN', ''], pd.NaT, inplace=True) 3. Convert Date Column Using pd.to_datetime(): Use the pd.to_datetime() function to convert the text to proper datetime objects. It’s flexible and can handle different date formats. You can specify the errors='coerce' argument to handle invalid parsing. python Copy code df['date_column'] = pd.to_datetime(df['date_column'], errors='coerce') errors='coerce': This will convert any unparseable values to NaT (missing value for dates). You can also use the format parameter if you know the exact format of your dates: python Copy code df['date_column'] = pd.to_datetime(df['date_column'], format='%d/%m/%Y', errors='coerce') 4. Handle Mixed or Unknown Formats: If your dataset has mixed formats, you can attempt to parse them flexibly without specifying the format, but be cautious as this may lead to incorrect parsing in ambiguous cases (e.g., 01/02/2023 could be 1st Feb or 2nd Jan depending on regional formats). python Copy code df['date_column'] = pd.to_datetime(df['date_column'], dayfirst=True, errors='coerce') 5. Check for Parsing Errors: After conversion, you can check if there are any rows that could not be converted and take further action (e.g., manually fixing them or dropping those rows). python Copy code invalid_dates = df[df['date_column'].isna()] print(invalid_dates) 6. Fill or Drop Invalid Dates: You can decide whether to fill invalid dates with a placeholder or drop them from the dataset entirely: python Copy code # Fill with a default date (e.g., today's date) df['date_column'].fillna(pd.Timestamp.today(), inplace=True) # Or drop rows with invalid dates df.dropna(subset=['date_column'], inplace=True) Example: python Copy code import pandas as pd # Sample dataframe data = {'date_column': ['12/01/2021', '31/12/2020', 'NULL', '15-03-2021', '2020/02/30']} df = pd.DataFrame(data) # Replace invalid date entries like 'NULL' with NaT df['date_column'].replace(['NULL', 'NaN', ''], pd.NaT, inplace=True) # Convert text to datetime, handle errors with 'coerce' df['date_column'] = pd.to_datetime(df['date_column'], errors='coerce', dayfirst=True) # Inspect the result print(df) By following these steps, you should be able to resolve date conversion errors and standardize the date format in your dataset.
Converting Mixed-Format Dates in Power Query Understanding the Problem: When importing CSV data into Power Query, it's common to encounter mixed date formats, especially when the data source isn't consistent. This can lead to errors when attempting to convert the data to a date data type. Solution: Identify the Formats: Use the Text.Format function to inspect the first few rows and identify the distinct date formats present. For example: Code snippet Table.TransformColumns(YourTable, {"DateColumn"}, each Text.Format(_, "yyyy-mm-dd")) Use code with caution. Replace "yyyy-mm-dd" with the appropriate format based on your data. Create a Custom Function: If you have multiple formats or complex logic, create a custom function to handle the conversion: Code snippet let ConvertDate = (dateText as text) as datetime => if Text.StartsWith(dateText, "MM/DD/YYYY") then DateTime.FromText(dateText, "MM/DD/YYYY") else if Text.StartsWith(dateText, "DD/MM/YYYY") then DateTime.FromText(dateText, "DD/MM/YYYY") else DateTime.FromText(dateText, "YYYY-MM-DD") in ConvertDate Use code with caution. Apply the Function: Use the Table.TransformColumns function to apply the custom function to the date column: Code snippet Table.TransformColumns(YourTable, {"DateColumn"}, each ConvertDate(_)) Use code with caution. Example: Assuming your date column is named "Date" and has formats like "MM/DD/YYYY" and "DD/MM/YYYY", you could use the following code: Code snippet let Source = Csv.Document(File.Contents("YourFile.csv"), [Delimiter=","]), #"Changed Type" = Table.TransformColumns(Source, {"Date"}, each try DateTime.FromText(_, "MM/DD/YYYY") otherwise DateTime.FromText(_, "DD/MM/YYYY")), #"Filtered Rows" = Table.SelectRows(#"Changed Type", each not IsError([Date])) in #"Filtered Rows" Use code with caution. Additional Tips: If you're unsure about the formats, you can use the Text.Format function to experiment with different formats until you find the correct ones. For more complex scenarios, you might need to use regular expressions or other advanced techniques. Consider using conditional logic or custom functions to handle edge cases or specific requirements. By following these steps, you should be able to successfully convert mixed-format dates in Power Query and avoid errors.
WHAT A TRAINER, HATS OFF TO THIS LADY, EVEN THOUGH I DIDN'T MISS THE SINGLE CONTENT AND FOR 5-7 HRS I CONTINUOUSLY SAT AND WATCHED THE VIDEO AND PARALLELLY PRACTICED THE SAME.
I REALLY LIKED THE VIDEO, YOU MADE MY ALL CONCEPTS CLEAR IN A SINGLE VIDEO AND MADE MY LIFE EASY TOO. THANK YOU SO MUCH
Thank you
Without a doubt the best power BI Video i have watch. The trainer is awesome
Thank You so much
Thank you for sharing this project very good understand and detail explain more gain insights about project.
Glad it was helpful!
This is called a real time project...🙏🏻
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Beautifully explained end to end execution of the project.The way she explained and the presentation was awesome.
Thank you so much, please subscribe our channel
honestly amazing !!! I was badly in search of this end to end project , tons of thanks to you !!
Great to hear!
Thanks to Uma and KSR Datavizon for this very informative session... I watched this session at the right time of my journey... I am very thankful to you guys... The way she explained every topic and how she was interacting was very impressive... Best session on Power BI i ever watched... 👏👏👏👏
Thank you so much for your kind words! We're glad you found the session helpful and engaging.
"why this is not working" hahahaha so cute. Jokes apart, excellent video, many thanks to the team and instructor. All in one video.
Thank You !
I had made this full project after seeing your video and I would like to thank you soo much that you made us understand the topics in a very easy way..
Thank you for all your efforts...👌👌👌
Most welcome 😊 Please subscribe our channel for regular updates
Thanks a lot! Every minute in it was valuable. Please add many more such end to end videos.
Thank you, We will
One video cleared all my doubts Thank you #KSR team 🙏🙏🙏
You are welcome
Best project never seen any other youtube channels 🎉
You're welcome! Glad it was helpful. Please subscribe our channel it motivates us a lot, Thank you in advance
Thanks a tonn.
I have been searching for such video for long time. Thanks a million for making this. This is so informative and helpful. Cleared all my doubts. 🙏
You're welcome! I'll be expecting a million-dollar check in the mail then!, Please subscribe our channel it motivates us a lot
@@KSRDatavizon mam can you provide total deccription too
Well explained. Even minor details also explained.
Thank You so much
Sooooper helpful and clear explanation. We want more videos like this on different domains...
Sure 👍
Very valuable n informative video
Thanks a lot
This video really helped me get my new job! Thank you so much for the valuable insights and guidance
Mam such wholistic end to end videos are really appreciated and helpful
Glad to hear that, Please subscribe our channel, it will motives to do more videos
Hi uma… you are amazing… the way you explain. Thank you so much for your inputs… love from Poland.
You are so welcome!, please subscribe our channel for regular updates
25:15 mark table as date- very important step and helped me gain my answer regarding my Query with date. Also if we try to implement same concept with different date columns, it won't be validated, because it consist of duplicate date values and not distinct once, hence this is also an additional reason for we to consider creating master_date_table as an independent dimension table.
What a trainer i had never seen before like this type of online class
very usefully completed full course and topics
greater to meet you✌👌👍
Thanks a ton
You are very nice trainer.. U mentioned each and every small concept in detailed manner. Thank you so much... Its very helpful to me... ❤❤❤
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Very much appreciate for insightful project
It's my pleasure, Please share and subscribe our channel, Thank you so much for your compliment.
Well-articulated , You covered end to end project with great patience, i must say you are an excellent tutor, Uma
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Wow amazing session the way uma explaining concepts is flawless enjoyed the complete session.
Looking forward to more interactive sessions like this.
Thank You 🤩👍
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Truly Insightful session, engaging and Instructor explaining the concepts in the simplest manner possible, very supportive and humble. Hats Off to you :). Also Thanks for making the premium content available for free.
Glad you enjoyed it! Please subscribe our channel for regular updates
Thanks for content like this, your project helped me to understand end to end approach of how power bi works. please add more videos. your work is really appreciatable.
Thanks, will do! ASAP
Detailed Explanation, Great Video
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Awesome Trainer, Hatsoff to the session creator. This module was very engaging, interesting.
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Let me begin by saying this first, The video is amazing.
Quick suggestion for calculating the number of active customers: The following DAX formula feels to me like a better fit. Given that it is the same table that we use for our purposes and is easy to read.
= CALCULATE(count(Bank_Churn[CustomerId]),Bank_Churn[IsActiveMember] = 1)
Similarly for the inactive members it can be easy to read as follows:
= CALCULATE(COUNT(Bank_Churn[CustomerId]),Bank_Churn[IsActiveMember] = 0)
Thank you for the amazing videos.
Nice bro good and Easy idea i got result through yours simple way DAX.
I appreciate your suggestion and I'm glad you found the video helpful!
Thanks a tonnnn. I have been searching for such video for long time. Thanks a million for making this. This is so informative and helpful. Cleared all my doubts. 🙏🙏🙏🙏🙏
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Good explain i could understand with uma mam brief lecture on project Mam i request you do more complete projects in different kinds of scenarios please...You have excellent teach skills nice english communication..
We will try to do more videos
1,000,000 of thanks to share this treasure of power bi video. I would like to study with you, if I would have the oportunity.
Again, thanks a lot.
Thanks
Really a Good session. Topics well covered and very useful
thank you so much for your feedback, will make more sessions on this. please subscribe for regular updates and it motivates us a lot
Tonnes of Thanks
Each concept explained in very simple manner
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Thank you so much. Your explanation is mind blowing.
You are most welcome, You are welcome! Please subscribe our channel, it motivates us
Amazing work hope will get some more in near future
Awesome session from this awesome teacher ...
thank you
Enjoyed a lot. Thanks for detailed explanation.
Amazing Trainer .
Thank you so much, please subscribe our channel for regular updates
Hi hope you are doing well This video helps us a lot and the way you explained is very detailed, and you are providing keen knowledge about Power Bi Thank you
So nice of you
Learned almost all in one class thank you
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Best project explanation in power bi
Thanks a lot
Thank you so much for the wonderful video. It's so simple to understand. Humble trainer. Hatts off..
You are most welcome
Very useful project I have been following your channel since year expecting few more different projects 👍👏👏
Thank you very much
Thankyou for this amazing project and to the point explaination!
You're very welcome! please subscribe our channel it motivates us to do more videos
omg very deep explaination, thank you so much ma'am
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Excellent discussion. Thank You
Our pleasure!
very helpful end to end project, thanks from UK
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Well its great display of Power BI learning skills, Cheers :)
Amazing explanation from the ksr team, Request you to make end to end project video on supply chain solutions (sales, CRM, procurement, finance, marketing, operations)
Thank you for the suggestion! We'll definitely consider creating an end-to-end project video on supply chain solutions.
Very UseFul. thank you
You are welcome
learnt Alot . Amazing project .Thanks team
Always welcome, please subscribe our channel for regular updates and it motivates us
Very useful information. Thanks for sharing this information. All my doughts were cleared. Thank you very much. Please do more videos like this.
Nice to hear
Very Nice and clear explanation
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Plz do more videos like this, thank you soo much for such an amazing content
sure, thank you so much for your valuable feedback, Please subscribe our channel, it will motives to do more videos
Good session that covers end to end content on a high level!!
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Good explaination mam,
please upload 1 more project.
Will upload soon
Nice madam you will complete information regarding power bi
thank you
Excellent tutorial.Thanks for sharing 👍
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Thank you very much 😊. Please Bring more end to end project videos🙏🙏🙏🙏
Sure sir will do
Wonderful video thanks
Thank You
Thanks a lot for this kind of great content mam, Hats of to your patience levels🙂
Thanks a lot
Very well explained. you deserve million subscribers. kindly make video on telecom end to end project
😍
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Thank you very much for End to end project.
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Great session
Thank you so much
Thanku mam for the wonderful session.❤
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very helpful information. well explained..thanks from DATA is FuturRe channel dedicated to Data Science
You are most welcome
Please also do in depth Sales Analysis like this one.
sure sir
Thanks Uma, well explained.
You are welcome 😊
so helpful, very nicely explained
Glad it was helpful!
It was very informative, Thank you so much!
Glad it was helpful!
Most awaited video... Thank you so much 🙏🥰
My pleasure 😊, Please subscribe our channel, it will motives to do more videos
its very interesting
UMA thank you so much .... it's really helpful..
You are most welcome, Please subscribe our channel it motivates us
Hello mam, can u upload one more new project bacuse its very helpful to us. I trid this project its very easy to learn nice and nice.
Requested to you pls uplaod another new topic project
Will upload soon
@@KSRDatavizon ok thnks.
I m doing internship now but we hv don't know abt projexlct and i saw your videos and i hav done your project bank domain so pls giv us one more project pls
Amazing 🔝
Please do one video for a pharmacy project.
clear explanation....thank you
You are welcome
Hi , thanks for giving this most valuable information this cleared some of doubts, i have question that when you created new table as calculation how its automatic connect with fact table?
Bcoz same Column name. as they used fact table "Date Column" if you remember.
Yes, you can
I have question that datemaster table values are being used for analysis exit of customer, "DOJ+Tenure",should be used for churn analysis.....but DateOfJoining has been used ???
we can do either way sir.. each biz defines own way of churn
Hi maam your explanation is good and i have to request you please increase when you write dax formula the screen is not visible so word not correct find out that
sure will make in future videos, thank you for letting us . please subscribe our channel for regular updates
hello i am unable to do the dax calculations can someone please help me with it i am getting an error saying that we cannot do the dax calculations if the data type is different but i made sure that both are in integers
Please reply here if anyone is familiar with this query
Troubleshooting Line Chart Sorting Issues
Understanding the Problem:
It seems that your line chart is interpreting the month names as text values, rather than dates, which is causing the sorting to be alphabetical instead of chronological.
Potential Solutions:
Ensure Correct Data Type:
Check the Column Properties: Right-click on the month column in your data source and verify that its data type is set to "Date" or a similar format. If it's set as "Text", change it to the appropriate date format.
Create a Date Table: If your month data is not in a date format, consider creating a separate date table with columns like "Year", "Month", and "MonthName". This can provide a cleaner and more efficient way to handle dates in your visualizations.
Sort Axis Manually:
Right-click on the Axis: In your line chart, right-click on the axis that contains the month names.
Select "Sort Axis": Choose the appropriate sorting option (e.g., "Sort Ascending" or "Sort Descending") based on your desired order.
Use a Calculated Column:
Create a Calculated Column: If you need more complex sorting logic, create a calculated column that assigns a numerical value to each month (e.g., 1 for January, 2 for February, etc.).
Sort by Calculated Column: Use this calculated column as the axis in your line chart to ensure proper sorting.
Example (Power BI):
If you're using Power BI, you could create a calculated column to assign a numerical value to each month:
Code snippet
MonthNumber = MONTH('YourTableName'[Month])
Use code with caution.
Then, use this "MonthNumber" column on the axis of your line chart.
Additional Tips:
Check for Formatting Issues: Ensure that your month names are formatted consistently (e.g., "January" vs. "Jan"). Inconsistent formatting can affect sorting.
Consider Regional Settings: If you're working with different regional settings, make sure that the month names are recognized correctly in your data source.
By following these steps and addressing the potential causes, you should be able to resolve the sorting issue in your line chart and ensure that the months are displayed in the correct order.
Please provide more details about your data source and visualization tool if you need further assistance.
Thank you madam...Very very good video...I can't find right end to end report with healthcare data or hospital data .Please upload one video with healthcare data analysis ...Thank you
I appreciate your kind words about the video. I'm glad you found it helpful.
I'm always looking for opportunities to create more videos on different topics, including healthcare data analysis. While I don't currently have a specific video dedicated to end-to-end analysis with healthcare data, I can provide some resources that may be helpful:
th-cam.com/video/ahQrhyKmxGI/w-d-xo.htmlsi=9gTVCxaV0aU1FKEV
Too Good Madam
Thanks a lot, please subscribe our channel it motivates us
Amazing explanation mam
Thanks a lot, Please subscribe our channel, it will motives to do more videos
@@KSRDatavizon could you plz make video on manage parameters .
Its a good video, but if you would have included the Data refresh after RLS , issues y it doesn't work in desktop and powerbi service it would be great... Errors and issues also has to be explained.. It will be helpful
Thanks for the tip, please subscribe our channel for regular updates
Too good
Thank you so much
very nice explanation...Could you plz made one video for data security using principle function
sure, will make those video shortly . than you.
Mam make a video on what key parameters we take for a businesses analysis
Sure mam will do asap
Very nice video...really helpful...
But while am trying to create Exit and retain customers measures am getting total customers values... Why?
pls post your measure calculation here.. there could be filter context error
Thanks a lot, really really helpful!!
Thank you for your kind words, they mean a lot to me! Please subscribe our channel for regular updates.. and its motivates us a lot ,, thanks again
Super training sister Garu....Pls make a video on roles and responsibility in ur powerBI project .....????
We already have uploaded in our channel. pls have a look at it
this is what i exactally want
I’m so glad to hear that this video met your needs! 😊 If you enjoyed it, please consider subscribing to our channel for more content like this. And if there’s anything specific you’d like to see in the future, feel free to let me know. Thanks for watching!
In the dataset provided date column is in text,if we change type i am getting errors.How to resolve this?
im facing the same
When you are dealing with a date column stored as text and get errors when converting it to a proper date format, it usually indicates inconsistencies or unexpected formats in the data. Here’s how you can approach this issue:
1. Inspect the Data Format:
First, check if there are any anomalies in the date format such as:
Mixed formats (e.g., DD/MM/YYYY vs. MM/DD/YYYY)
Missing or invalid dates (e.g., "NULL", "NaN", or empty strings)
Incorrect characters or symbols
You can inspect the unique date formats using the following code (assuming you're using Python and pandas):
python
Copy code
df['date_column'].unique()
2. Handle Missing or Invalid Dates:
You need to either clean or remove the rows with missing or invalid dates. You can replace them with a default value, such as NaT (Not a Time), or you can drop them entirely.
python
Copy code
df['date_column'].replace(['NULL', 'NaN', ''], pd.NaT, inplace=True)
3. Convert Date Column Using pd.to_datetime():
Use the pd.to_datetime() function to convert the text to proper datetime objects. It’s flexible and can handle different date formats. You can specify the errors='coerce' argument to handle invalid parsing.
python
Copy code
df['date_column'] = pd.to_datetime(df['date_column'], errors='coerce')
errors='coerce': This will convert any unparseable values to NaT (missing value for dates).
You can also use the format parameter if you know the exact format of your dates:
python
Copy code
df['date_column'] = pd.to_datetime(df['date_column'], format='%d/%m/%Y', errors='coerce')
4. Handle Mixed or Unknown Formats:
If your dataset has mixed formats, you can attempt to parse them flexibly without specifying the format, but be cautious as this may lead to incorrect parsing in ambiguous cases (e.g., 01/02/2023 could be 1st Feb or 2nd Jan depending on regional formats).
python
Copy code
df['date_column'] = pd.to_datetime(df['date_column'], dayfirst=True, errors='coerce')
5. Check for Parsing Errors:
After conversion, you can check if there are any rows that could not be converted and take further action (e.g., manually fixing them or dropping those rows).
python
Copy code
invalid_dates = df[df['date_column'].isna()]
print(invalid_dates)
6. Fill or Drop Invalid Dates:
You can decide whether to fill invalid dates with a placeholder or drop them from the dataset entirely:
python
Copy code
# Fill with a default date (e.g., today's date)
df['date_column'].fillna(pd.Timestamp.today(), inplace=True)
# Or drop rows with invalid dates
df.dropna(subset=['date_column'], inplace=True)
Example:
python
Copy code
import pandas as pd
# Sample dataframe
data = {'date_column': ['12/01/2021', '31/12/2020', 'NULL', '15-03-2021', '2020/02/30']}
df = pd.DataFrame(data)
# Replace invalid date entries like 'NULL' with NaT
df['date_column'].replace(['NULL', 'NaN', ''], pd.NaT, inplace=True)
# Convert text to datetime, handle errors with 'coerce'
df['date_column'] = pd.to_datetime(df['date_column'], errors='coerce', dayfirst=True)
# Inspect the result
print(df)
By following these steps, you should be able to resolve date conversion errors and standardize the date format in your dataset.
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sure, will make those, videos. few sessions already available in our website.
Hii mam
Which power bi licence do you have used in this particular end to to project
51:44 why in line chart, months are not in chronological order like jan, feb, march etc......they are at random whe i try to do it
Facing the same problem.I hope you found the solution. Please help if you got the solution.
the first report clustered column chart is not working as expected
To provide a comprehensive solution, I'll need more context about the specific issues you're encountering with your clustered column chart in Power BI
After importing the csv bank churn, the dates are mixed format. Power query gives errors when converting to date.
Converting Mixed-Format Dates in Power Query
Understanding the Problem:
When importing CSV data into Power Query, it's common to encounter mixed date formats, especially when the data source isn't consistent. This can lead to errors when attempting to convert the data to a date data type.
Solution:
Identify the Formats:
Use the Text.Format function to inspect the first few rows and identify the distinct date formats present. For example:
Code snippet
Table.TransformColumns(YourTable, {"DateColumn"}, each Text.Format(_, "yyyy-mm-dd"))
Use code with caution.
Replace "yyyy-mm-dd" with the appropriate format based on your data.
Create a Custom Function:
If you have multiple formats or complex logic, create a custom function to handle the conversion:
Code snippet
let
ConvertDate = (dateText as text) as datetime =>
if Text.StartsWith(dateText, "MM/DD/YYYY") then
DateTime.FromText(dateText, "MM/DD/YYYY")
else if Text.StartsWith(dateText, "DD/MM/YYYY") then
DateTime.FromText(dateText, "DD/MM/YYYY")
else
DateTime.FromText(dateText, "YYYY-MM-DD")
in
ConvertDate
Use code with caution.
Apply the Function:
Use the Table.TransformColumns function to apply the custom function to the date column:
Code snippet
Table.TransformColumns(YourTable, {"DateColumn"}, each ConvertDate(_))
Use code with caution.
Example:
Assuming your date column is named "Date" and has formats like "MM/DD/YYYY" and "DD/MM/YYYY", you could use the following code:
Code snippet
let
Source = Csv.Document(File.Contents("YourFile.csv"), [Delimiter=","]),
#"Changed Type" = Table.TransformColumns(Source, {"Date"}, each try DateTime.FromText(_, "MM/DD/YYYY") otherwise DateTime.FromText(_, "DD/MM/YYYY")),
#"Filtered Rows" = Table.SelectRows(#"Changed Type", each not IsError([Date]))
in
#"Filtered Rows"
Use code with caution.
Additional Tips:
If you're unsure about the formats, you can use the Text.Format function to experiment with different formats until you find the correct ones.
For more complex scenarios, you might need to use regular expressions or other advanced techniques.
Consider using conditional logic or custom functions to handle edge cases or specific requirements.
By following these steps, you should be able to successfully convert mixed-format dates in Power Query and avoid errors.