New to Spark and Synapse....Need to do some transformation including adding a columns, changing datatypes, etc. I am reading a csv into a dataframe. I'd like t
Be the following DataFrame in python pandas: date time_SEL time_02_SEL_01 time_03_SEL_05 other 2022-01-01 34756 233232 3432423 756 2022-01-03 23322 4343 3334 3
I have a big data and I want to duplicate each row just below the original column by changing just one column value I want to copy the previous row value in pl
I have a problem. I have two date fields fromDate and toDate. The toDate also contains a timestamp, e.g. 2021-03-22T18:59:59Z. The problem is that I want to cal
I am trying to obtain the closest previous data point every hour in a pandas data frame. For example: time value 0 14:59:58 15 1 15:00:10 2
I have a numeric column ("value") in a dataframe ("df"), and I would like to generate a new column ("valueBin") based on "value." I have the following condition
although the same question has been asked multiple times. I dont seem to make it work. I use python 3.8 and I rean an excel file like this df = pd.read_excel(r"
although the same question has been asked multiple times. I dont seem to make it work. I use python 3.8 and I rean an excel file like this df = pd.read_excel(r"
I have a dataframe having many columns, 2 of them being 'App' and 'Reviews'. I discovered that for the same app there are multiple rows because they differ in t
Be the following DataFrames in python pandas: | date | counter | |-----------------------------|------------------| | 2022-01-0
I have set of columns need to be merged into single column where some columns have data and some don't have where it should be joined with the data to single co
I have a tuple that has data for several categories. Now I want to extract small dataframes from this tuple for each category based on a list I created. I want
I have a data frame that looks like this: Tag 0 skip_1 1 run 2 skip_1 3 run 4 skip_1 5
I have a dataframe and I would like to maintain information. My data frame is like: a <- c("a","b", "c", "d") b <- c("e","f", "g", "h") c <- c(1, 2, 1,
I've been looking for other similar issues on this ValueError, but none of them has the same code as I have. So here it is. As I am still very new at this, I am
I have a pandas dataframe df in which I have a column named time_column which consists of timestamp objects. I want to calculate the number of seconds elapsed f
How to obtain the below result. Sample Data with Output Time To default is the column which is to be calculated. We need to get the increment number as Time to
I have a pandas dataframe containing one column and a datetime index, i need to group the data by hour and keep each obsevation (record) for each of the grouped
I cannot use read_csv method of pandas properly on kaggle. Error that I get is: ParseError: Error tokenizing data. C error: Buffer overflow caught - possible ma
In the below JSON array { "data": [ { "name": "page_call_phone_clicks_logged_in_unique", "period": "lifetime", "values": [ {