I got an issue, hopefully someone has a great solution.
I am reading an Excel file. And I use keep_default_na=False because there is a productname called "NA" and I dont want pandas changing it to NaN.
df = pd.read_excel('Import_orders.xlsx',…
I found significant processing time difference in fillna for different column selection techniques of pandas dataframe.
Time taken for fillna of dataframe, whose columns are selected using loc
df1 = df.copy()
t1 = time.time()
df1.loc[:, col] =…
Here is an exctract of my dataset :
Dataset
Here is an exemple of dataset
df = pd.DataFrame(
{'vals': np.where(np.arange(35) < 30, np.arange(35), np.nan)},
index=pd.date_range('2021-01-01', freq='12H', periods=35))
…
I have a DataFrame like this:
>>> df = pd.DataFrame({'a': list('ABCD'), 'b': ['E',np.nan,np.nan,'F']})
a b
0 A E
1 B NaN
2 C NaN
3 D F
I am trying to fill NaN with values of the previous column in the next row and dropping this…
I would like to find rows in df where C contains X1 and replace value in A with value in C and, replace value in C with value in result1(shift values in C and result1 to the leftmost).
df:
A C result1 result2
0 NaN X1 …
Having issues with fillna() and df slices. Still have my python training wheels on and would appreciate any assistance. I've found lots of close examples on SE, but because of the conditionals and multiple columns I haven't found anything that…
Say I have a vector ValsHR which looks like this:
valsHR=[78.8, 82.3, 91.0]
And I have a dataframe MainData
Age Patient HR
21 1 NaN
21 1 NaN
21 1 NaN
30 2 NaN
30 2 NaN
24 3 NaN
24 …
I have 3 columns in the dataframe. object, id and price. I want fill
the blanks by reading the id column and discover which price should I
use. For exemple: If the id ends in (A,B or C) the price should be 30
but if it's end (7A,7B or 7C) the…
I have a dataframe similar to below:
col1 col2 col3 col4
0 101 1000 NaN NaN
1 102 2000 51 1500
2 103 2500 52 2800
3 104 3600 53 NaN
4 105 2400 NaN NaN
5 106 …
I searched a lot here for an answer that could solve this but couldn't find. The desired result is to fill only gaps when the extremities are equal values, limited to lengths of 4 values:
My dataset:
0 NaN
1 NaN
2 NaN
3 5.0
4 …
I'm trying to replace NaN values in my dataframe using:
values = {'pitch_type': 'UN', 'px': -1, 'pz': -1, 'pitch_type_prev': -1,'px_prev': -1,
'pz_prev': -1}
df_sample.replace(np.nan, values)
It fills all but two values. The returned…
I have a housing dataframe:
where there are missing values in the Price column. I wish to fill the missing values by the mean price in the respective suburb.
This is my code for filling up the mean price by the same…
I have a dataframe where the index is date increasing and the columns are observations of variables. The array is sparse.
My goal is to propogate forward in time a known value to fill NaN but I want to stop at the last non-NaN value as that last…
I found this behavior of resample to be confusing after working on a related question. Here are some time series data at 5 minute intervals but with missing rows (code to construct at end):
user value total
2020-01-01 09:00:00…