In the MWE below, I show my attempt to line-plot trips (from my df aggregated per month): I realised in my df, some trips contains jump (maybe due to data log), so they should be merged into single trip before aggregation. In the given df example above (before grouping). User 154 does undertake 2-trips, not 3. First started at 10:10:00
Tag: dataframe
Manipulating DataFrame
I have the following dataframe df where there are 3 columns: Date, value and topic. I want to create a new dataframe df1 where the topic is the column and is indexed by day, and each topic has its own value per day. My problem is that I don’t know how to match the value to the topic per day.
Python looping over a list to check if any of the list elements are equal to variable values in pandas dataframe
I have a pandas dataframe and I want to create a new dummy variable based on if the values of a variable in my dataframe equal values in a list. How can I create a new dummy variable for the dataframe, called variable 3, that equals 1 if variable 2 is present in the list and 0 if not? I
Pandas apply function to each row by calculating multiple columns
I have been stacked by an easy question, and my question title might be inappropriate. I want to calculate (df.amount * df.con)/df.groupby(‘name’).agg({‘amount’:’sum’}).reset_index().loc(df.name==i).amount) (Sorry, this line will return error, but what I want is to calculate total concentration (under each name) based on each ingredient amount and ingredient con. Here is my code: output: Any short-cut for this calculation? Thanks ahead.
importing for loop output to another for loop
I am facing problem while importing the output of a for-loop to another for loop. My python script Actually facing problem in this line of code e = {d[0]: c, d[1]:[2.0,2.0]}, where value of c should be different but by this script i am getting repeated value. Answer Your problem is that you keep over writting the value if c
how to drop rows with ‘nan’ in a column in a pandas dataframe?
I have a dataframe (denoted as ‘df’) where some values are missing in a column (denoted as ‘col1’). I applied a set function to find unique values in the column: I am trying to drop these ‘nan’ rows from the dataframe where I have tried this: However, the column rows remain unchanged. I’m thinking that the above repeated ‘nan’ values
pandas dataframe loc usage: what does supplying length of index to loc actually mean?
I have read about dataframe loc. I could not understand why the length of dataframe(indexPD) is being supplied to loc as a first argument. Basically what does this loc indicate? Answer That is simply telling pandas you want to do the operation on all of the rows of that column of your dataframe. Consider this pandas Dataframe: Your transformation df.loc[len(df),
Pandas filter without ~ and not in operator
I have two dataframes like as below I would like to do the below a) Check whether the ID and Name from df1 is present in df2. b) If present in df2, put Yes in Status column or No in Status column. Don’t use ~ or not in operator because my df2 has million of rows. So, it will result
Multiply pandas dataframe with a differently shaped dataframe based on condition
I have a pandas DataFrame (df_A) with this basic form: Furthermore I have another DataFrame (df_B): What I want to do is multiply the values of the second DataFrame with the values of the first, where the alt value is the same. I also do not want the d or e columns to be involved in the multiplication. So I
Calculate column value count as a bar plot in Python dataframe
I have time series data and want to see total number of Septic (1) and Non-septic (0) patients in the SepsisLabel column. The Non-septic patients don’t have entries of ‘1’. While the Septic patients have first ‘Zeros (0)’ then it changes to ‘1’ means it now becomes septic. The data looks like this: HR SBP DBP SepsisLabel Gender P_ID 92