after creating the data. it is tuple and after converting tuple into pandas dataframe so i got 9 features (columns) but when i try to insert 9 cols it says. ValueError: Shape of passed values is (2, 1), indices imply (2, 9) Basically i wanna generate data and convert it into pandas dataframe but could not get to it. error
Tag: dataframe
python – Append dataframe but remove null column from each table
I have two dataframes in python: df1 Column1 Column2 Column3 Column4 Column5 1a 123 RJ 12.1 test1 2a 432 MT 23.2 test3 3a 234 DR 34.3 test5 df2 Column1 Column3 Column6 1a RJ 695 2a MT 568 3a DR 232 And I wish to append them together and save them as CSV, separated by pipe. But when I simply append,
Splitting a dataframe with many labels
I’m trying to split my data by different labels, like this: And this works fine for small amounts of numbers. However, I want to do this for many values. for example: This spits outs an error: ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all(). I’ve read the other questions with this error,
Test for First Occurrence of Conditions in Python Dataframe
Background Pretty new to Python and dataframes. I’m on a Mac (Sierra) running Jupyter Notebook in Firefox (87.0). I’ve got a dataframe like this: I want to add a Boolean column to this dataframe that checks whether a) the price in this row is zero and b) if it’s the first occurrence of a zero price for this subgroup (reading
How to add a row for subtotal from each group and then a final row of grand total of entries
I have the following dataframe: Location Student Name D Amy D Raj E Mitch F Poo F Mack I am trying to generate the following dataframe: Location Student Name D Amy D Raj Total Students at D 2 E Mitch Total Students at E 1 F Poo F Mack Total Students at F 2 Grand Total 5 How do I
Select all row where all columns are equal to value
I have a pandas dataframe and I need to select the rows where all the columns are equal to 0.00. How can I do that? Answer First, we’ll setup some example data to work on – here there are 3 columns, but it could be more, or fewer in your example. And define a function that accepts a row from
How to convert to API response with multiple levels to dataframe in python
I have response from API call as shown below How can I convert this into proper dataframe. I tried below code its creating the columns are properly. I want each element of the API response as seperate column. For eg. ‘position’: {‘lat’: 47.464699, ‘lon’: 8.54917} should be created dedicated column for lat and Lon seperately. Loop Locations and get values
In Pandas dataframe, how to append a new column of True / False based on each row’s value?
I’m trying to create a dataframe of stock prices, and append a True/False column for each row based on certain conditions. The original 9 rows by 4 columns dataframe contains only the close / open / upper / mid columns. that check_conds functions returns the df nicely with the new cond1-5 columns returning True / False appended for each row,
Python mutiply pandas dataframe containing scientific and float values with a float
It’s getting error due to scientific values in df, please let me know if any one has any suggestions or help to fix this? Error: Answer I guess you’re getting this issue because of type. you can try to convert the column to float type –
Column merge and shift elements in a Dataframe row
I have a dataframe as follows: In the last row (and several others in the full dataframe) the negative signs are misplaced. My question is if a negative sign is there at i-th position then it should merge i+1 th element and shift all other row elements to the left such that it the final output should be Answer Setup