Explode data in a list not separated by comma Question: Let’s say have the following database: {‘docdb_family_id’: {0: 569328, 1: 574660, 2: 1187498, 3: 1226468, 4: 1236571, 5: 1239098, 6: 1239277, 7: 1239483, 8: 1239622, 9: 1239624, 10: 1239749, 11: 1334477, 12: 1340405, 13: 1340418, 14: 1340462, 15: 1340471, 16: 1340485, 17: 1340488, 18: 1340508, …
What is equivalent of Matlab nan( ) in python? Question: this is my MATLAB code with the following output: pad=nan(1,5) pad = NaN NaN NaN NaN NaN I want to do the same operation in python, I tried np.isnan(1,6) but this is not working. what should I used to get the same results. thank you …
dataframe succesive projection of one type onto the other using pad Question: In a process we construct different types of objects, e.g. of type R and Q. One type (R) shall then be projected onto the other type (Q) successively. The data generation as an example. import pandas as pd import numpy as np np.random.seed(42) …
why is pd.crosstab not giving the expected output in python pandas? Question: I have a 2dataframes, which I am calling as df1 and df2. df1 has columns like KPI and context and it looks like this. KPI Context 0 Does the company have a policy in place to man… Anti-Bribery PolicynBroadridge does not toler… 1 …
python pandas dataframe : fill nans with a conditional mean of previous and next value Question: I have the following dataframe: | col1 | col2 | col3 | | 5 | 3 | 9 | | NaN | 6 | NaN | | NaN | 3 | 7 | | 7 | 8 | 5 …
nan values when creating a pd.Series through a function Question: Assume we have the following dataframe ap_comp = pd.DataFrame({‘Name’: [‘Troll’, ‘Legolas’],’Code’: [111, 222]}) and I passed it through the following function a_mapping = pd.Series(apcompl[‘Code’], index=apcompl[‘Name’]).to_dict() my question is why the a_mapping returns as {‘Troll’: nan, ‘Legolas’: nan} why the nan appears? Should’ t it be …
Counting the number of pandas.DataFrame rows for each column Question: What I want to do I would like to count the number of rows with conditions. Each column should have different numbers. import numpy as np import pandas as pd ## Sample DataFrame data = [[1, 2], [0, 3], [np.nan, np.nan], [1, -1]] index = …
Python – aggregate groupby multiple columns, skipping nan cells Question: I’m trying to aggregate a dataframe accross multiple columns, grouped by Date. Some cells contain nan, which I would like to keep. So my df looks like this: import random import numpy as np import pandas as pd rng = [‘2015-02-24′,’2015-02-24′,’2015-02-24′,’2015-02-24′,’2015-02-24′,’2015-02-24’, ‘2015-02-25′,’2015-02-25′,’2015-02-25′,’2015-02-25′,’2015-02-25′,’2015-02-25’] rng = pd.to_datetime(rng) …
Updating column value based on nan value of other column Question: I have this simple function with 2 columns. What I’m trying to do is to check what group has a number of nan and change it to a new desired value. Here’s a code snippet: def twod_array(): data = {"group": [-1, 0, 1, 2, …
Replace nan with zero or linear interpolation Question: I have a dataset with a lot of NaNs and numeric values with the following form: PV_Power 2017-01-01 00:00:00 NaN 2017-01-01 01:00:00 NaN 2017-01-01 02:00:00 NaN 2017-01-01 03:00:00 NaN 2017-01-01 04:00:00 NaN … … 2017-12-31 20:00:00 NaN 2017-12-31 21:00:00 NaN 2017-12-31 22:00:00 NaN 2017-12-31 23:00:00 NaN 2018-01-01 …
