michaelboerman

library(stringr)
library(dplyr)

convert_feature_name <- function(feature_str) {
  # Pattern that matches all possible formats
  pattern <- "^rr_(dlnq_\\d{1,3}_\\d{1,3}|dlnq_121plus|not_dlnq)_" %>%
    paste0("(dlnq_\\d{1,3}_\\d{1,3}|dlnq_121plus|not_dlnq|term_x)_(\\d{1,3})_(\\d{1,3})")

  parts <- str_match(feature_str, pattern)

michaelboerman

When your company blocks meme generator websites (and no one reads my nested READMEs anyways)

https://i.imgflip.com/7qcsn9.jpg

michaelboerman

import pandas as pd
import numpy as np
from datetime import datetime

def compare_dataframes(df1, df2):
    # Check if one object is a dataframe with datetime64[ns] dtype and the other is a list of strings
    if isinstance(df1, pd.DataFrame) and df1.dtypes.all() == 'datetime64[ns]' and isinstance(df2, list):
        # Convert the list of strings to datetime64[ns] format
        df2_values = np.array([np.datetime64(datetime.strptime(date_str, '%Y-%m-%d')) for date_str in df2])
    elif isinstance(df2, pd.DataFrame) and df2.dtypes.all() == 'datetime64[ns]' and isinstance(df1, list):