I have the following pandas pivot table: table = pd.pivot_table(df, index = ‘group’, columns = ‘levels’, values = ‘uid’, aggfunc = ‘count’, margins = True) There are three levels (level 1, level 2, and level 3). Basically I have individuals that progress through these levels, but I want to know what percentage of people make… Read More Pandas Pivot Table add subsequent columns then divide by previous column

I have my df as below: df I want to convert into df2 as below: df2 I have been trying with panda, but still not able to achieve my targeted aim. This is my sample code: df = pd.read_excel(‘PathV1.xlsx’) df1 = pd.DataFrame(df, columns=[‘source’]) df1[[‘target’]] = pd.DataFrame(df1[‘source’].str.split(‘:’).tolist()) df1[‘index’] = df1.index// 3 df2 = df1[[‘source’, ‘target’, ‘index’]].pivot(columns=’source’,… Read More convert data elements in data frame via long to wide format using Panda

I have this dataset called x for example: client_id a b c 1 1 0 0 2 0 1 1 3 0 0 1 4 1 1 1 I then want to create another table, that calculates the number of times each column from a to c had 1, in combination of other columns having… Read More Cross table of several columns in R

My csv contain like (df) : item_group item_code total_qty total_amount cost_center 0 Drink IC06-1P 1 3.902 Cafe II 1 Drink IC09-1 1 2.927 Cafe II 2 BreakFast FS04-2 1 6.463 Cafe II 3 Drink IC08-1 1 2.927 Cafe II 4 Drink DT05-1 1 2.561 Cafe II .. … … … … … 79 Standard Food… Read More how to pivot table from excel to pandas

I am looking for a solution to sort a pandas pivot table, as it is possible in Excel pivot tables, according to the aggregated values and thereby determine the order of the first level. I have found a solution that uses pd.append. A warning tells me that pd.append will not be available in the future… Read More Sorting in Multi-Layers – Pandas pivot_table

I would like to get a dataframe of counts from a pandas pivot table, but for the aggregate function to include every index. For example df1 = pd.DataFrame({"A": ["foo", "bar", "shtuff"], "B": ["one", "two", "one"], "C": [1, 2, 3]}) df2 = pd.DataFrame({"C": [1,2,2,1,2,1,1,2,2], "D": ["A", "B", "A", "B", "A", "B", "A", "C", "A"]}) df =… Read More pandas pivot_table to include every index

I’m trying to pivot this dataframe without success > head( data_shape, 15) # A tibble: 15 x 5 COD_REG apqual num_pen pens_mean pens_mean_real <int> <int> <int> <dbl> <dbl> 1 16 116 843. 7.69 1 15 674 1309. 11.9 2 15 36 1496. 13.6 2 16 3 1200 10.9 3 15 917 1494. 13.6 3 16… Read More dplyr & dataset: how to pivot?

I’m trying to create a pivot table with multiple columns; I’m unsure how to explain this better. But the following is the desired output, dataframe setup, and code I have tried so far. Desired Output: Dataframe Setup: data = { ‘WholesalerID’: {0: 121, 1: 121, 2: 42, 3: 42, 4: 54, 5: 43, 6: 432,… Read More Creating a pivot table with multiple columns

Hello I have a large dataframe where I have need to update or fill in the missing values. The condition is that the correct value should be in respect to row name matching to a column name. For example: df <- data.frame( ID = c("x", "y", "z"), x = c("1", "0.45", "0.47"), y = c("0.45",… Read More Update records of dataframe where row names equal to column names

I have created a pivotable in pandas with multilevel columns, but the order of columns are not sorted – Year 2022 2021 2023 Month Jan Feb Mar Jan Dec Jun What I want: Year 2021 2022 2023 Month Jan Mar Jan Feb Jun Dec How can I get the above order? >Solution : The (best?)… Read More Pandas sort multilevel columns with year and month