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You start with 100 and a year later you have 105. It is easy to figure out the growth rate there. But what if you make monthly contibutions, or withdraw at random times and the period is not exactlly one year?
Before using, you should:
- Optionally have a CSV file containing the dates and amounts of contibutions/withdrawals. The file sould be formatted as the first column date in format YYYY-MM-DD and the second column the numeric amounts (withdrawals as negative numbers).
- Columns should be separated by a tab.
- Additional columns are allowed for comments, but they are not processed.
Calculates the Gini index of all the numbers your csv file.
- Have your numbers in a csv file. The cells included in the calculation should be able to be converted to a number (do not include currency symbols). The file may contain other (text) cells, they are discarded.
- Identify the separator. Tab ( ), Comma (,), Semicolon (;) or Pipe (|).
Gives you overview of your text. It gives you the count of each word, and the count of each letter. It also gives the counts of each character pair, so you would know exactly what letters appear together most frequently in your text.
- Have your whole text in a simple txt file.
- Decide if it should convert special characters into ascii characters or not.
i.e. Should 'Hôtel' be converted into 'Hotel' or not?
You are given a database export in multiple CSV files. Next time you receive the same set and are asked "What changed?" Now it is your are task to go through all these tables and each cells, and mark down any changes.
There must be a better solution — there is!
Before using, you should:
- Have all your CSV files zipped together in a zip file.
- Identify all index columns (e.g. "Record ID", or a combination like "User ID" + "Test ID").
- Optionally define a sort order if records arrive in an inconsistent sequence.
- Optionally exclude columns that change constantly and are not relevant (e.g. "Last modified at").
- Identify the separator. Tab ( ), Comma (,), Semicolon (;) or Pipe (|).
- Make sure all your tables have the same format.
You are handed a large set of CSV files but your workflow requires Excel. Instead of opening each file and saving it as .xlsx one by one, this tool converts the entire set in one run — either as separate Excel files or combined into a single multi-tab workbook.
You have better things to do with your time, let the robots handle the conversion.
Before using, you should:
- Have all your CSV files zipped together in a zip file.
- Identify the separator. Tab ( ), Comma (,), Semicolon (;) or Pipe (|).
- Make sure all your tables have the same format.
- Decide if you want to have one file per CSV or all tables merged into one file, one table per tab.
You have a table with large amounts of data from your database. But now there has been an amendment and the new dataset is has some new columns added or removed. Now your task is to merge the tables together into one combined dataset and you need to align the columns of old and new sets.
This could take hours if not a whole day. Maybe you can delegate this task to a compute.
Before using, you should:
- Have your CSV files named in alphabetical order so, it wuould reflect the chronological order.
i.e. AB_v1.csv, AB_v2.csv, AB_v3.csv ... - Have them all in one zip file for easy upload.
- Identify the separator. Tab ( ), Comma (,), Semicolon (;) or Pipe (|).
- Make sure all your tables have the same format.
You need some randomly generated data to test some processes. And you need to test with large datasets. But it is bothersome to generate the tables manually.
This tool allows you to generate up to 99 tables, up to 99 data columns, 1 to 4 index columns and a maximum of 9999 rows per table. Smaller tables are also possible. Data can have full entry, or some gaps or even sparcely populated.
Data is generated randomly, as are data types per column assigned randomly. Available data types are: text, numbers (integer or with some decimal places), date, time, pass/fail
Before using, you should:
- Have an idea how big of a dataset you would like to have. Other aspects of the dataset will be out of your control.
You are given a database export in multiple CSV files. Next time you receive the same set and are asked "What changed?" Now it is your are task to go through all these tables and each cells, and mark down any changes.
There must be a better solution — there is!
Before using, you should:
- Have all your CSV files zipped together in a zip file.
- Identify all index columns (e.g. "Record ID", or a combination like "User ID" + "Test ID").
- Optionally define a sort order if records arrive in an inconsistent sequence.
- Optionally exclude columns that change constantly and are not relevant (e.g. "Last modified at").
- Identify the separator. Tab ( ), Comma (,), Semicolon (;) or Pipe (|).
- Make sure all your tables have the same format.
You are handed a large set of CSV files but your workflow requires Excel. Instead of opening each file and saving it as .xlsx one by one, this tool converts the entire set in one run — either as separate Excel files or combined into a single multi-tab workbook.
You have better things to do with your time, let the robots handle the conversion.
Before using, you should:
- Have all your CSV files zipped together in a zip file.
- Identify the separator. Tab ( ), Comma (,), Semicolon (;) or Pipe (|).
- Make sure all your tables have the same format.
- Decide if you want to have one file per CSV or all tables merged into one file, one table per tab.
You have a table with large amounts of data from your database. But now there has been an amendment and the new dataset is has some new columns added or removed. Now your task is to merge the tables together into one combined dataset and you need to align the columns of old and new sets.
This could take hours if not a whole day. Maybe you can delegate this task to a compute.
Before using, you should:
- Have your CSV files named in alphabetical order so, it wuould reflect the chronological order.
i.e. AB_v1.csv, AB_v2.csv, AB_v3.csv ... - Have them all in one zip file for easy upload.
- Identify the separator. Tab ( ), Comma (,), Semicolon (;) or Pipe (|).
- Make sure all your tables have the same format.
You need some randomly generated data to test some processes. And you need to test with large datasets. But it is bothersome to generate the tables manually.
This tool allows you to generate up to 99 tables, up to 99 data columns, 1 to 4 index columns and a maximum of 9999 rows per table. Smaller tables are also possible. Data can have full entry, or some gaps or even sparcely populated.
Data is generated randomly, as are data types per column assigned randomly. Available data types are: text, numbers (integer or with some decimal places), date, time, pass/fail
Before using, you should:
- Have an idea how big of a dataset you would like to have. Other aspects of the dataset will be out of your control.
You start with 100 and a year later you have 105. It is easy to figure out the growth rate there. But what if you make monthly contibutions, or withdraw at random times and the period is not exactlly one year?
Before using, you should:
- Optionally have a CSV file containing the dates and amounts of contibutions/withdrawals. The file sould be formatted as the first column date in format YYYY-MM-DD and the second column the numeric amounts (withdrawals as negative numbers).
- Columns should be separated by a tab.
- Additional columns are allowed for comments, but they are not processed.
Calculates the Gini index of all the numbers your csv file.
- Have your numbers in a csv file. The cells included in the calculation should be able to be converted to a number (do not include currency symbols). The file may contain other (text) cells, they are discarded.
- Identify the separator. Tab ( ), Comma (,), Semicolon (;) or Pipe (|).
Gives you overview of your text. It gives you the count of each word, and the count of each letter. It also gives the counts of each character pair, so you would know exactly what letters appear together most frequently in your text.
- Have your whole text in a simple txt file.
- Decide if it should convert special characters into ascii characters or not.
i.e. Should 'Hôtel' be converted into 'Hotel' or not?