How to convert more than 3 level N nested dictionary to levelled dataframe? what I expect: index level_0 level_1 value 0 .Stock .No_0 3241512 1 .Stock .No_1 1111111111 2 .Stock .No_2 444444444444 3 .Stock .Version 46 4 .Stock .Revision 78 5 .Time NaN 12.11.2022 Firsly I need to convert nested dictionary to list of levelled dictionaries, than lastly convert list
Tag: pandas
Extrapolating time series data into the future by repeating/scaling existing values
I have hourly data on electricity consumption for a specific day. I would like to use this data to “predict” the hourly electricity consumption for the following days. The value for the following day should be the value from the same hour the day before, multiplied by a scaling factor f (e.g. 2). The dataframe df that I have looks
Break line chart on the plot
I have a dataframe with a column for weeks and data captured for each week. it looks like this Now I am plotting a line chart with this data . Notice that from week 23 to week 40, we didnt have data. so my intention is to skip this weeks on the plot and only have a line chart of
Python algo trading pandas data clean up and call from another function
I have below code and is working fine when I am executing from console. Now I want convert the code constructor which will help to call this and get data. Now I need to convert above code to constructor and call from another function. Which should return the pandas data frame. Expected out put is, when we call the constructor
Replace span tags with whitespace or parse contents as new column with pandas.read_html
I want to scrape Congressional stock trades from Capitol Trades. I can scrape the data, but the column that contains stock tickers has a span tag that separates company names from company tickers. pandas.read_html() removes this span tag, which concatenates company names and tickers and makes it difficult to recover tickers. For example, company names that end with an “INC”
Pandas: filter on grouped and aggregated dataframe
I have a dataframe which is based on a read-in excel list. The data has multiple columns and rows with one unique identifier. I want to plot the data through a PyQT interface based on some user selection (checkboxes), but I cannot select one unique row for plotting. The data looks like this: After I get this: I can use
pandas split values in column
I’m new to pandas (version 1.1.5) and have tried str.split() and str.extract() to split column POS of numerical values with no success. My dataframe is about 3000 lines and is structured like this (note _ and – delimiters in subset): I would like for the dataframe to look like this (i.e. retain values preceding all delimiters): My attempts have either
having error while using ‘Series’ object has no attribute ‘ix’
refer this image (https://i.stack.imgur.com/yLm32.png)](https://i.stack.imgur.com/yLm32.png) Answer I believe .iloc is used for Series instead of .ix.
(python) subtract value in a list from value in the same list in a for loop / list comprehension
suppose i have in a for loop I want to subtract the value i from the value that comes right after. In the above example: 4-3, 6-4, 8-6, 13-8. (and i want to skip the first value) desired result can i do this in a for loop / list comprehension? more specifically do I want to do this in a
using set() with pandas
May I ask you please if we can use set() to read the data in a specific column in pandas? For example, I have the following output from a DataFrame df1: where the first column is the index.. I tried first to isolate the second column using the following: x = pd.DataFrame(df1, coulmn=[0]) Then, I transposed the column using the