Here are my data and index value image :
As in the snap pandas Dataframe returning two values. What could be possibly wrong? I am beginner, sorry for the bad editing.
I think I see the issue.
data['Title'].iloc[0]
Try something like this. I think the .head() portion of the code is causinng you issues
Related
I am creating two dataframes, that I set equal to eachother based on an index field. So each frame has the same indices on both sides and I sort them as well. I want to return the differences between these fields, so as to catch any of the rows that have 'updated' since the last run. But I am getting a weird result.
df1.compare(df2)
I fail to see any differences here, and when I manually look at the id's involved I do not see any changes at all. What could be causing this?
If you look at the below code:
It's working.
Can you please share both of your dfs so that we can assist you better.
I solved it and will post this in case someone else gets stuck. Apparently Nulls were being interpreted as 'None' when read into the dataframe. But the other dataframe actually had the String 'None' vs null. You would never know this by pulling these into dataframes, as they would look identical to the eye.
It took me a while to realize this and hopefully this saves someone else some time.
enter image description here
I am facing problem in converting DataFrame A to DataFrame B. I have tried using the .transpose() method. However, it did not work. Please help if you can. I cannot share the code, as it is confidential.
Please check these functions:
melt
explode
stack
Also, converting your df (or parts of it) to dictionary may be useful: to_dict.
I am trying to format a pandas DataFrame value representation.
Basically, all I want is to get the "Thousand" separator on my values.
I managed to do it using the pd.style.format function. It does the job, but also "breaks" all my table original design.
here is an example of what is going on:
Is there anything I can do to avoid doing it? I want to keep the original table format, only changing the format of the value.
PS: Don't know if it makes any difference, but I am using Google Colab.
In case anyone is having the same problem as I was using Colab, I have found a solution:
.set_table_attributes('class="dataframe"') seems to solve the problem
More infos can be found here: https://github.com/googlecolab/colabtools/issues/1687
For this case you could do:
pdf.assign(a=pdf['a'].map("{:,.0f}".format))
I'm learning dataframe now. I've been stuck in how to get a subset of a dataframe or table with its label index. I know it's a very simple question but I couldn't find the solution in pandas documentation. Hope someone could help me. Appreciate your help.
So, I have a dataframe named df_teams like below:
enter image description here
If I want to get a subtable of a specific team 'Warriors', I can use df_teams[df_teams['nickname']=='Warriors'], resulting a row in the form of dataframe. My question is, what if I want to get a subtable of more teams, say I want information of both 'Warriors' and 'Hawks' to form a new table? Can I do something similar by using logical index and finishing in one line of code?
You could do a bitwise or on the two conditions using the '|' character.
df_teams[(df_teams['nickname']=='Warriors')|(df_teams['nickname']=='Hawks')]
Alternatively if you have a list of values you want to check against you could instead use the isin method to return rows that have one of the values present in the list.
E.g
df_teams[df_teams['nickname'].isin(['Warriors','Hawks'])]
I'm using the function del df['column name'] to delete the column in Pandas but there is the error as the attached picture. I have no idea why it does not work. Much appreciated for any help to solve the problem.
You should use the drop method instead.
df.drop(columns='column_name')
And if you want to chage the original Dataframe you should add the inplace=True as an argument to the method.
Also, avoid posting pictures if possible. Posting the written code is often more usufel and makes it easier for someone to help you!