I am reading a csv file into pandas. This csv file consists of four columns and some rows, but does not have a header row, which I want to add. I have been trying the following: But when I apply the code, I get the following Error: What exactly does the error mean? And what would be a clean way
Tag: dataframe
How to read a Parquet file into Pandas DataFrame?
How to read a modestly sized Parquet data-set into an in-memory Pandas DataFrame without setting up a cluster computing infrastructure such as Hadoop or Spark? This is only a moderate amount of data that I would like to read in-memory with a simple Python script on a laptop. The data does not reside on HDFS. It is either on the
Pandas dataframe from nested dictionary
My dictionary looks like this: I want to get a dataframe that looks like this: I tried calling pandas.from_dict(), but it did not give me the desired result. So, what is the most elegant, practical way to achieve this? EDIT: In reality, my dictionary is of depth 4, so I’d like to see a solution for that case, or ideally,
How to remove string value from column in pandas dataframe
I am trying to write some code that splits a string in a dataframe column at comma (so it becomes a list) and removes a certain string from that list if it is present. after removing the unwanted string I want to join the list elements again at comma. My dataframe looks like this: So basically my goal is to
How to add a constant column in a Spark DataFrame?
I want to add a column in a DataFrame with some arbitrary value (that is the same for each row). I get an error when I use withColumn as follows: It seems that I can trick the function into working as I want by adding and subtracting one of the other columns (so they add to zero) and then adding
Iterating through pandas groupby groups
I have a pandas dataframe school_df that looks like this: Each row represents one project by that school. I’d like to add two columns: for each unique school_id, a count of how many projects were posted before that date and a count of how many projects were completed before that date. The code below works, but I have ~300,000 unique
How to switch columns rows in a pandas dataframe
I have the following dataframe: I tried with pivot table but I get the following error: any alternative to pivot table to do this? Answer You can use df = df.T to transpose the dataframe. This switches the dataframe round so that the rows become columns. You could also use pd.DataFrame.transpose().
Remove name, dtype from pandas output of dataframe or series
I have output file like this from a pandas function. I’m trying to get an output with just the second column, i.e., by deleting top and bottom rows, first column. How do I do that? Answer You want just the .values attribute: You can convert to a list or access each value:
Shuffle DataFrame rows
I have the following DataFrame: The DataFrame is read from a CSV file. All rows which have Type 1 are on top, followed by the rows with Type 2, followed by the rows with Type 3, etc. I would like to shuffle the order of the DataFrame’s rows so that all Type’s are mixed. A possible result could be: How
Python Pandas replace NaN in one column with value from corresponding row of second column
I am working with this Pandas DataFrame in Python. I need to replace all NaNs in the Temp_Rating column with the value from the Farheit column. This is what I need: If I do a Boolean selection, I can pick out only one of these columns at a time. The problem is if I then try to join them, I