My df has USA states-related information. I want to rank the states based on its contribution. My code: Expected Answer: Compute state_capacity by summing state values from all years. Then Rank the States based on the state capacity My approach: I am able to compute the state capacity using groupby. I ran into NaN when mapped it to the df.
Tag: dataframe
Pandas conditional counting by date
I want to count all orders done by each customer at each order date, to find out how many orders were done at the time of each order. Input: Expected output: The following code works but is extremely slow. Taking upwards of 10 hours for 100k+ rows. There is certainly a better way. Answer Try sort_values to get dates in
python string concatenation following a sequence
What would be the most pythonic way of creating the following string concatenation: We have an initial dataframe with some of the columns being: origin dest_1_country dest_1_city dest_2_country dest_2_city dest_3_country dest_3_city dest_4_country dest_4_city We want to create an additional column that is the full route for every row in the dataframe and that could be generated by df[‘full_route’] = df[‘origin].fillna(“”)
pyspark – filter rows containing set of special characters
I have a data frame as follow:- Now I want to find the count of total special characters present in each column. So I have used str. contains function to find it, though it is running but it does not find the special characters. Answer You may want to use rlike instead of contains, which allows to search for regular
How to plot a column value with its index as axis
I have a data frame df: In reality, I have 50 rows in the data frame. To make it simple I am representing it here with only 3 rows. I am interested in illustrating the correlation between ColumnA and ColumnB that is given in df[‘correlation’]. What would be the best possible way to do so? One of the choices may
Format the extracted covid vaccine data from website
Trying to format the “Vaccine data” from URL to pandas dataframe https://www.mygov.in/sites/default/files/covid/vaccine/covid_vaccine_timeline.json Here is the parent website https://www.mygov.in/ Sample output I am trying to extract the data in the below format in my data frame Answer
Is there an easy way to establish a hierarchy between entities using only 2 ID fields?
I have a table with 2 fields like so: Account_ID Parent_ID x y x1 y x2 y y z y1 z y2 z z z z a z1 a a a b b The IDs fields are both in int64 format. The first field represents accounts which could be controlled by a parent account which could be itself controlled by
Create a DataFrame from a XML File
im new to XML and i want to know how to create a dataframe in python from this XML file. I have the following code, it creates the DataFrame but when i tried to append the value of the row, i dont know why it keeps coming “None”. I dont know if i have to change de calling argument i.e
Python DataFrame: Map two dataframes based on day of month?
I have two dataframes. month_data dataframe has days from start of the month to the end. student_df with each student’s only present data. I’m trying to map both dataframes so that the remaining days left for each student should be marked as absent month_data month_data = pd.DataFrame({‘day_of_month’:pd.date_range(’01/01/2021′,’31/01/2021′)}) student_df final_df Answer You can create a new dataframe containing all dates and
Is there a function to write certain values of a dataframe to a .txt file in Python?
I have a dataframe as follows: Basically I would like to write the dataframe to a txt file, such that every row consists of the index and the subsequent column name only, excluding the zeroes. For example: The dataset is quite big, about 1k rows, 16k columns. Is there any way I can do this using a function in Pandas?