I have a dataframe as follows: And I want to convert this dataframe as follows: I tried a few things but nothing worked. Any ideas? Answer Use Series.str.get_dummies with DataFrame.stack: If order is important:
Tag: dataframe
How drop duplicate rows based on a time delta whilst keep the latest occurrence of that record?
I have a table in the form: ID DATE_ENCOUNTER LOAD 151336 2017-08-22 40 151336 2017-08-23 40 151336 2017-08-24 40 151336 2017-08-25 40 151336 2017-09-05 50 151336 2017-09-06 50 151336 2017-10-16 51 151336 2017-10-17 51 151336 2017-10-18 51 151336 2017-10-30 50 151336 2017-10-31 50 151336 2017-11-01 50 151336 2017-12-13 62 151336 2018-01-03 65 151336 2018-02-09 60 Although the dates are not
Reference DataFrame value corresponding to column header
I am trying to append a column to my DataFrame that is based on the values that are referenced by indicated column names. I have the following DataFrame: The values under “Select” are referencing the values that are under the column number that “Select” shows. For example, for row 0, “Select” shows 4, which refers to the value under column
How do I extract the last trading day from a csv file?
I have a csv file which contains 30 years of stocks data. A portion of it looks like this: How can I extract the last trading date of a specific month of a specific stock, say the last trading month of June 2018 of stock s_0003? This is my code, but it doesn’t seem to be working for me because
Filter and calculate % of a dataframe column
I am trying to calculate the % of men and women in a dataframe column named “gender”. “gender” is defined as an object taking 3 values : “Man” “Woman” “nan” (NA). I did this : But it returns 0.0% for both. When i check ‘total’ value it returns : 10123033 but zero for both ‘men’ and ‘women’ Thanks. Answer pay
How do I melt a pandas dataframe?
On the pandas tag, I often see users asking questions about melting dataframes in pandas. I am gonna attempt a cannonical Q&A (self-answer) with this topic. I am gonna clarify: What is melt? How do I use melt? When do I use melt? I see some hotter questions about melt, like: Convert columns into rows with Pandas : This one
inserting missing categories and dates in pandas dataframe
I have the following data frame. I want to add in all score levels (high, mid, low), for each group (a, b, c, d), for all dates (there are two dates – 2020-06-01 and 2020-06-02) I can add in the score categories for all subjects with the following, but i am having trouble adding date in as well the expected
how to apply Pandas.set_option (Python) to pandas.style objects
I have noticed that when we set some options for pandas DataFrames such as pandas.DataFrame(‘max_rows’,10) it works perfectly for DataFrame objects. However, it has no effect on Style objects. Check the following code : Which will result in : I do not know how to set the properties for Style object. Thanks. Answer Styler is developing its own options. The
Is there anyway to convert specific text data to csv format and give Header names in python?
I have this format of the dataset in a text file. Here the dataset link is https://drive.google.com/file/d/1RqU2s0dqjd60dcYlxEJ8vnw9_z2fWixd/view?usp=sharing I want to give the left side value as column name and right side values will be a row format. Output should be I have tried with text to CSV but not working Answer The simplest way I know is: read data file
pandas.Dataframe equivalent for Pandas.read_csv converters?
This discussion covers the differences between dtypesand converters in pandas.read_csv function. I could not find an equivalent to converters for the pandas.DataFrame constructor in the documentation. If I build a dataframe directly from a list of lists, what would be the best way to mimic the same behavior? Some made-up example: output: What would be the best way to get