Category "dataframe"

Create multiple boolean columns in pandas dataframe based on multiple conditions

I have a dataset, where authors are ranked by the order of authorship (1, 2, 3, etc). Authorid Author Article Articleid Rank 1 John article 1

How do I create a list containing new data frames from an existing data frame?

I have a csv file containing 5 columns, 225 rows containing my data. The columns pertain to the experiments' Subject_ID, treatment (9 types), replicate(5), time

How to keep columns header on excel without change after export data to excel file?

I work on sql server 2017 I run script depend on python language v 3.10 . I need to export data to excel fileStudentExport.xlsx already exist, and keep header w

Use of Replace() in Python Dataframe for Multiple Columns but same value

Query: I need to replace the 1 old value with the 1 new value for a bunch of columns (not all columns) in a dataframe. The question is about the syntax to be us

Transforming data using Python Pandas (or M) in Power Query for PowerBi

I have some data about projects I would like to transform in a way that makes it easier to analyse with PowerBi. The data looks like this: Project Number Proje

creating new column in dataframe with the values from another column in the same dataframe [duplicate]

As a scientific researcher I am a beginner in Python. I am trying to make a new column in the following dataframe:

PySpark read data into Dataframe, transform in sql, then save to dataframe

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

Apply change to timedelta to columns containing a given string

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

How to duplicate each row having only one column different than the previous row pandas data frame?

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

Calculate the difference in days between two date fields

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

Select previous row every hour in pandas

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

Error - replacement has [x] rows, data has [y]

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

convert float64 (from excel import) to str using pandas

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"

convert float64 (from excel import) to str using pandas

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"

Deleting multiple rows under same App Name but with different number of reviews

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

Perform a merge by date field without creating an auxiliary column in the DataFrame

Be the following DataFrames in python pandas: | date | counter | |-----------------------------|------------------| | 2022-01-0

Concat null columns data with actual data in pandas?

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

pandas, creating dataframes based on tuple

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

Count occurrences within a specific range

I have a data frame that looks like this: Tag 0 skip_1 1 run 2 skip_1 3 run 4 skip_1 5

Multiply without eliminate information

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,