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2024-03-12 06:30:04
You can use DataFrame.with_row_index(): import polars as pl df = pl.DataFrame({"test": np.arange(1, 11)}) print( df.with_row_index() .with_columns( pl.when(pl.col("index") < 5)...
Tags: python pandas dataframe
2024-03-12 14:00:05
Add parameter quoting to pd.read_csv and to df.to_csv with 3 (QUOTE_NONE): # Load CSV data into dataframes df = pd.read_csv(StringIO(csv_data), header=0, dtype=str,...
Tags: python pandas
2024-03-12 16:00:06
df[df["Column"].str.contains("
Tags: python pandas dataframe
2024-03-12 17:00:06
If you have datetime/time objects in Excel, the easiest might be to import as string, add the reference date when missing, convert to_datetime and subtract the reference: df = pd.read_excel('data.xlsx...
Tags: python pandas excel
2024-03-12 20:00:06
You could melt with ignore_index=False, then set the new variable column as index with set_index append=True: out = (data.melt(data.columns[:-3], ignore_index=False, var_name='tail') .set_i...
Tags: python pandas multi-index
2024-03-12 20:30:04
You can achieve it by checking if the number of days in the month is equal to the total number of hours in that month. If they are equal, it means that the month is completed. By comparing the length...
Tags: python pandas
2024-03-12 21:00:10
Try this: In this solution, groupby() will return a series, with the values in A as sets, with the values of B as the index. We then check to see if each set is equal to the target set. Lastly we map...
Tags: python pandas
2024-03-12 22:30:08
First check whether the elements you want to select are contained in response / soup; the ones you are addressing do not appear to be present. So your ResultSet soup.find_all('a', class_='entry-title'...
Tags: python pandas web-scraping
2024-03-13 00:00:06
You can melt and post-process the columns: out = (df .melt('ID', ignore_index=False) .assign(ID=lambda d: d['ID'].mask(d['variable'].eq('Value2'), 'Value2')) .sort_index().drop(columns='varia...
Tags: python pandas dataframe
2024-03-13 00:00:07
Assuming rule_df the rules DataFrame and df the data one: # first ensure the correct column names are used # and that dates are in a YYYY-MM-DD format tmp = (df.rename(columns={'Height(in)': 'Height'}...
Tags: pandas dataframe dynamic

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