WebApr 8, 2024 · IIUC, there is a pandas builtin to do that : factorize.. pandas.factorize(values, sort=False, use_na_sentinel=True, size_hint=None) Encode the object as an enumerated type or categorical variable. This method is useful for obtaining a numeric representation of an array when all that matters is identifying distinct values.. df["Description_new"] = … WebAug 3, 2024 · In contrast, if you select by row first, and if the DataFrame has columns of different dtypes, then Pandas copies the data into a new Series of object dtype. So selecting columns is a bit faster than selecting rows. Thus, although df_test.iloc[0]['Btime'] works, df_test.iloc['Btime'][0] is a little bit more efficient. –

How to Convert a List to a DataFrame Row in Python?

WebCreate pandas DataFrame with example data. Method 1 : Convert float type column to int using astype () method. Method 2 : Convert float type column to int using astype () method with dictionary. Method 3 : Convert float type column to int using astype () method by specifying data types. Method 4 : Convert string/object type column to int using ... josh candies allentown

python - Convert columns into rows with Pandas - Stack …

WebIn the case of two values, it appears that you only want the first (e.g. the last row of your example). You can use loc to first set the second value to None in the case both columns … Webdf['month']=np.nan for month in [col for col in df.columns if 'month' in col]: df['month'].fillna(df[month],inplace=True) It first creates an empty column named "month" with NaN values, and you fill the NaN with the values from the "monthX" columns, concretely it gives you: WebSep 16, 2024 · The following code shows how to convert the ‘points’ column in the DataFrame to an integer type: #convert 'points' column to integer df ['points'] = df ['points'].astype(int) #view data types of each column df.dtypes player object points int64 assists object dtype: object. how to lay flagstones on soil