Advertisements I want to subset a df by returning the first and last consecutive value from a pandas col. Drop_duplciates won’t work because it doesn’t account for consecutive groupings. I’m using .shift() (below) but this only returns the last consecutive value, where I want the first and last. import pandas as pd df = pd.DataFrame({"Item":[‘A’,… Read More subset first and last consecutive value from pandas df col – python

Advertisements Have a following DataFrame: df = pd.DataFrame({"booking": [‘A’, ‘B’, ‘C’], "route": [[‘1′,’2′,’3’],[‘5′,’4′,’1’],[‘3′,’6′,’8′]]}) need to insert into each "route" cell the ‘0’ at the beginning of list to get this: df1 = pd.DataFrame({"booking": [‘A’, ‘B’, ‘C’], "route": [[‘0′,’1′,’2′,’3’],[‘0′,’5′,’4′,’1’],[‘0′,’3′,’6′,’8’]]}) and next step is to split route by legs, to get this: df1 = pd.DataFrame({"booking": [‘A’, ‘B’,… Read More Insert element into list of Pandas Dataframe

Advertisements I have my dataframe df_daily and I’d like to check for duplicates based on my date column which corresponds to df_daily[0] and those rows that would be duplicates due to having the same date I’d like for them to be deleted and maintain only what is not a duplicate. I tried the following but… Read More Getting a syntax error when I want to delete row based on column value

Advertisements let us suppose i want to analyze tourism visitors in different regions/cities of Georgia(Country), here is simple for getting data from the following site : https://www.geostat.ge/en/modules/categories/101/domestic-tourism import pandas as pd data =pd.read_excel("https://geostat.ge/media/52189/visits-by-visited-region.xlsx",skiprows=[0]) data.dropna(axis=0,inplace=True) data.drop(["Year","Quarter","Total","Other regions"],axis=1,inplace=True) data["Country"] ="Georgia" print(data.head()) result is : Tbilisi Adjara A/R Imereti … Kvemo Kartli Shida Kartli Country 0 314.835582 106.598779… Read More Convert multi column table into two column

Advertisements Hi i want to convert my dataframe from df = pd.DataFrame({ ‘date’: [ ‘2019-08-01’, ‘2019-12-01’, ‘2019-23-01’, ‘2019-15-01’, ‘2020-26-02’, ‘2020-10-10’, ‘2020-08-10’, ‘2021-01-04’ ], ‘loc’: [ ‘axp’,’axp’, ‘axp’, ‘axp’, ‘axe’, ‘axp’, ‘axp’, ‘axe’ ], ‘category’: [ ‘domestic’, ‘domestic’, ‘domestic’, ‘domestic’, ‘wild’, ‘domestic’, ‘domestic’, ‘wild’ ], ‘status’: [ ‘found’, ‘found’, ‘not found’, ‘found’, ‘found’, ‘found’, ‘found’, ‘not… Read More Resampling and grouping in more than one pandas column

Advertisements I am turning a dict into a dataframe. My dict is like key:[value]. Dict example; {‘StringAwesome’: PureWindowsPath(‘//server/cool.log’), ‘StringCool’: PureWindowsPath(‘//server/rad.log’)} I want three rows like; 0 — key — value I used orient=index. Which is close, but it gives me; 0 key — value I’d like to end up with; index — columnA — columnB… Read More How do I turn a dictionary into a 3 column dataframe?

Advertisements I have a dataset with 600 rows. the data has one main ID= Version and second ID= Task. Data looks like this: Version Task Concept Att 1 – Att 2 – 1 1 1 3 2 1 1 2 1 1 1 2 1 2 3 1 2 2 1 2 1 3 1… Read More combine rows with the same IDs into the same row

Advertisements Dictionaries have an update method which can be used to add new items based on those of another dictionary. Here it is an example: d1 = {"asd": 0, "lol": 1} d2 = {"lol": 2, "foo": 3} d1.update(d2) assert d1 == {‘asd’: 0, ‘lol’: 2, ‘foo’: 3} I am trying to obtain a similar result… Read More Dictionary update method for DataFrames

Advertisements I want to drop rows based on index values, but I don’t mean listing them. I want to see if there is a way where I could not list down the years manually. I want to drop the rows with indices below 2000, is there anyway to do this with a formula, im thinking… Read More How to drop rows based on value of index

Advertisements Consider the following pandas series: import pandas as pd s = pd.Series([0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1]) I want to identify the first block of 1 values. The block starts when 0 switches to 1 for the first time and ends when it switches… Read More Identify first block in a pandas series based on switching values