There are a few times when I have a dictionary (not very large) and try to convert it into a dataframe, the code above would yield one with each cell being NaN. Yet the code below works fine. I wonder what could be the difference? Answer What are your dictionary keys? I am guessing the keys don’t align to your
Tag: dataframe
How to use apply() to change data in a pandas data frame to lowercase?
I have this pandas dataframe: And what I want to do is use apply() with a function to convert all the data to lowercase. I couldn’t find anything on the internet showing how to do this, I am currently stuck with this. however it gives me error that series object has no attribute lower. Any help greatly appreciated! Thanks! Answer
How to check if a substring in a pandas dataframe column exists in a substring of another column in the same dataframe?
I have a dataframe with columns like this: I want to create a list with values from A that matches values from B. The list should look like [- 5923FoxRd, Saratoga Street, Suite 200…]. What is the easiest way to do this? Answer To make a little go a long way, do the following: Create a new series for each
Groupby for value before previous row
How do i add a boolean if the value is lower than the value for the row above, per fruit? And if so the average of the previous 5 years Answer Try this: Output:
Delete empty dataframes from a list with dataframes
This is a list of dataframes. I am trying to delete the empty dataframes from the above list that contains dataframes. Here is what I have tried: which gives: Important:It needs to store them in the data variable as well Answer We ca use filter or list comprehension
Data_Frame Error – ValueError: Can only compare identically-labeled Series objects
I have two data_frames, as below: The task is to create a data_frame(below one), where I need to add df_marks[‘Int1/40’] & df_marks[‘Int2/40’], if df_name[‘Student_ID’] == df_marks[‘Student_ID’] I tried But its giving error as, Do we have any simple way to do this? Regards, Deepak Dash Answer Use DataFrame.join with aggregated sum for new column in df_name: Or solution without helper
Have only 1 record per date in a pandas dataframe
Background: In mplfinance, I want to be able to plot multiple trade markers in the same bar. Currently to my understanding you can add only 1 (or 1 buy and 1 sell) to the same bar. I cannot have 2 more trades on the same side in the same bar unless I create another series. Here is an example: df
How to check the folder for file and then read the file in python
I need to read a csv from a folder location, but there is catch in it. It could also happen my other module which writes the csv into that folder fails and unable to export the file, so basically i have to check the folder that if a csv file called “test.csv” exist or not in that folder, if it
Pandas DataFrame: Fill NA values based on group mean
I would like to update the NA values of a Pandas DataFrame column with the values in a groupby object. Let’s illustrate with an example: We have the following DataFrame columns: We’re simply measuring temperature multiple times a day for many months. Now, let’s assume that for some of our records, the temperature reading failed and we have a NA.
Is there a function to search a value in a pandas cell list, and return the rows if the value is solitary or the only type?
I have the follow dataframe: I’m trying to return an output that would tell me all of the tasks & IDs where ‘Coolant’ is in the ‘Type’. But, only the tasks & IDs where coolant isn’t mixed with any other type. I think my expected output would be a dataframe like this: Could somebody have a go at it? Also,