I have the following df: df = pd.DataFrame({‘A’: [0.0137, 0.1987, ‘NaN’, 0.7653]}) Output: A 0 0.0137 1 0.1987 2 NaN 3 0.7653 I am trying to format each row from column A, using .iloc (because I have many columns in my actual code) into, e.g. 1.37%. However, If I perform df.iloc[:, 0] = (df.iloc[:, 0]… Read More Only format df rows that are not NaN

I have the following df: df = pd.DataFrame({‘A’: [‘foo’, ‘bar’], ‘B’: [134.532, 543.009], ‘C’: [1.98, 0.9], ‘D’: [300.99, 7000.89] }) Output: A B C 0 foo 134.532 1.98 1 bar 543.009 0.90 I want to format/round every row of the columns B and C to have 0 decimal places. I do not want to change… Read More How to format the rows of only selected columns of df

I have a pandas dataframe whose first column is string representation of timeseries. I would like to convert this column into datetime object using the following line of code: df[‘Timestamp’] = pd.to_datetime( df[‘Timestamp’], format=’%m-%d-%Y %H:%M:%S’).dt.strftime(‘%Y-%m-%d %H:%M:%S’) I want to preserve the format in the datetime object to be month first and year last but I… Read More How to convert string timeseries to datetime object in a dataframe while preserving the format of the original datetime?

I’m having trouble understanding the point of {} since when I see it, it’s used the same way as a print("",variable,""). I’ve only learned about it today and it’s used like this: print("planet:{}".format(Human.place)) Human is a class and place a variable that’s introduced by the class Human >Solution : Given: x = 5 str1 =… Read More What's the point of {} followed by format and how to use it in python?

My data contain a bunch of floats, which I’d like to format as follows: Thousand separator is a dot Decimal separator is comma Always show two decimals add Euro sign This is what I got so far: import pandas as pd df = pd.DataFrame({‘x’: [1.50, 2.3456, 10000.22, 100.3, 6800]}) df[‘x’].map(‘{:.2f} €’.format) This yields 0 1.50… Read More Pandas Formatting with Currency sign, custom thousand separator and custom decimal separator

I have an empty dataframe of 14 rows with nan values created as below: dfs_empty_rows = pd.DataFrame(data=[[np.nan] * len(interm_df.columns)] * 14, columns=[np.nan] * len(interm_df.columns)) I want to concat interm_df, which was values with dfs_empty_rows so that the forst 14 rows are blank in the new dataframe. I am trying to concat using: pd.concat([dfs_empty_rows,df], axis=0, ignore_index=True)… Read More Concat empty data frame with another Dataframe in pandas with python

‘I would like to format a datetime object within df.query(). The following command works for me df.query(””2001-01-01′<eventdate”’) where eventdate is a multi index column in df. However, I cannot get the following to work m=’2001-01-01′ df.query(f”'{m}<eventdate”’) which reads the error invalid syntax. I have tried the following with no luck. ts=pd.Timestamp m=’2001-01-01′ df.query(f”’@ts({m})<eventdate”’) Any suggestions… Read More Formatting datetime object in df.query(), Python

I need to convert 13-04-2023 to MMM Do YYYY in javascript moment(ResData.mDate).format("MMM Do YYYY") I tried like above. But it gives output as Oct 14th 0018.how I fix this? >Solution : This is working: const o = moment(“13-04-2023”, “DD-MM-YYYY”); const s = o.format(“MMM Do YYYY”); console.log(s); //=> Apr 13th 2023 <script src=”https://cdnjs.cloudflare.com/ajax/libs/moment.js/2.18.1/moment.min.js”></script&gt;

Should i format variables like this: String type = null; String name = null; int age = 0; double weight = 0; boolean isFly; boolean isWalk; boolean isSwim; Or like this: String type = null, name = null; int age = 0; double weight = 0; boolean isFly, isWalk, isSwim; And may you give me… Read More What is the better way to design variables?