How to assign a variable in a column given another variable? [duplicate] - pandas

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Conditional Replace Pandas
(7 answers)
Adding a new pandas column with mapped value from a dictionary [duplicate]
(1 answer)
Closed 3 years ago.
This is my dataset :
Datset example
I want to assign to the different values* such as 'W M I HOLDINGS CORP' and 'MILESTONE SCIENTIFIC INC' another variable in the column 'ticker' in order to have the opportunity to sort them.
In the column 'ticker' I need to add WMIH and WLSS respectively to the two different values.
How can I do that ?
I am going to expect the output with something like this :
Output Example


You should be ok with this. Assuming you have your dataset in df variable.
df.loc[df['comnam'] == 'W M I HOLDINGS CORP', 'ticker'] = 'WMIH'
df.loc[df['comnam'] == 'MILESTONE SCIENTIFIC INC', 'ticker'] = 'WLSS'

Related

An array contains two objects, how can they be merged? [duplicate]

This question already has answers here:
Perform .join on value in array of objects
(14 answers)
Closed 4 months ago.
skills = [
{skill_id: 1, skill_name: “IT”},
{skill_id: 2, skill_name: “cooking”}
]
Desired output:
IT, Cooking
I have tried to use merge() to merge the two objects. However, I cannot seem to get the desired output.

You can use map() to transform array values like
const values = skills.map(skill => skill.skill_name);

Hey can anybody tell me what is the meaning of this? [duplicate]

This question already has answers here:
What is [:,:-1] in python? [duplicate]
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Python Difference between iloc indexes
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Understanding slicing
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Closed 6 months ago.
X = df_census.iloc[:,:-1]
y = df_census.iloc[:,-1]
what is the meaning of [:,:-1] in this and also [:,-1]

Following your example: [:,:-1]
The first argument is : which means to get all rows of the dataframe, and :-1 means to return all columns but the last one
In the case of just -1, it means to get the last column

Writing to csv makes column without being written [duplicate]

This question already has an answer here:
Pandas to_csv call is prepending a comma
(1 answer)
Closed 1 year ago.
I am trying to do math on a specific cell in a csv file with pandas, but whenever I try to do it, it adds a column on the left that looks like
,
1,value,value
2,value,value
3,value,value
4,value,value
5,value,value
So if I run it multiple times it looks like
,
1,1,1,value,value
2,2,2,value,value
3,3,3,value,value
4,4,4,value,value
5,5,5,value,value
How do I make it not do this??
My code is: add_e_trial = equations_reader.at[bank_indexer_addbalance, 1] = reciever_amount

Whenever you do a df.to_csv, include index=False. The left most column is the index of the dataset
df.to_csv(index=False)

How to change pandas Period Index to lower case? [duplicate]

This question already has an answer here:
Convert pandas._period.Period type Column names to Lowercase
(1 answer)
Closed 4 years ago.
I have a dataframe where I used
df.groupby(pd.PeriodIndex(df.columns, freq='Q'), axis=1).mean() to combine all column names from month into quarter by taking the mean.
However, the result dataframe has columns like below and I could not change all upper case Q into lower case 'q'.
PeriodIndex(['2000Q1', '2000Q2', '2000Q3', '2000Q4', '2001Q1', '2001Q2',
'2001Q3', '2001Q4', '2002Q1', '2002Q2', '2002Q3', '2002Q4',
'2003Q1', '2003Q2', '2003Q3', '2003Q4', '2004Q1', '2004Q2',
'2004Q3', '2004Q4', '2005Q1', '2005Q2', '2005Q3', '2005Q4',
'2006Q1', '2006Q2', '2006Q3', '2006Q4', '2007Q1', '2007Q2',
'2007Q3', '2007Q4', '2008Q1', '2008Q2', '2008Q3', '2008Q4',
'2009Q1', '2009Q2', '2009Q3', '2009Q4', '2010Q1', '2010Q2',
'2010Q3', '2010Q4', '2011Q1', '2011Q2', '2011Q3', '2011Q4',
'2012Q1', '2012Q2', '2012Q3', '2012Q4', '2013Q1', '2013Q2',
'2013Q3', '2013Q4', '2014Q1', '2014Q2', '2014Q3', '2014Q4',
'2015Q1', '2015Q2', '2015Q3', '2015Q4', '2016Q1', '2016Q2',
'2016Q3'],
dtype='period[Q-DEC]', freq='Q-DEC')
I have tried using df.columns=[x.lower() for x in df.columns] and it gives an
error:'Period' object has no attribute 'lower'

This looks like a duplicate of the issue posted here: Convert pandas._period.Period type Column names to Lowercase
Basically, you'll want to reformat the Period output to have a lowercase q like so:
df.columns = df.columns.strftime('%Yq%q')
Alternatively, if you want to modify your PeriodIndex object directly, you can do something like:
# get the PeriodIndex object you pasted in your question
periods = df.groupby(pd.PeriodIndex(df.columns, freq='Q'), axis=1).mean()
# format the entries accordingly
periods = [p.strftime('%Yq%q') for p in periods]
The %Y denotes the year format, the first q is the lowercase "q" you want, and the %q is the quartile.
Here is the documentation for a Period's strftime() method, which returns the formatted time string. At the bottom they have some nice examples!
Looking at the methods listed in the Pandas documentation, lower() isn't an available method for the Period object, which is why you're getting this error (a PeriodIndex is just an array of Periods, which denote a chunk of time).

Check if pandas column contains all zeros [duplicate]

This question already has answers here:
How do I delete a column that contains only zeros in Pandas?
(4 answers)
Closed 5 years ago.
I'm doing a complex calculation on a data frame that is bound to throw exceptions if all the values in a column are zeros. How to do a quick check whether a column is full of zero? i.e. return True if the column has values other than 0 else False.

you can do something like this:
(df['col'] == 0).all()
This will return True if all values are 0 otherwise it will return false