This question already has answers here:
Select data when specific columns have null value in pandas
(3 answers)
How to select rows with one or more nulls from a pandas DataFrame without listing columns explicitly?
(6 answers)
Closed 4 years ago.
I want to select rows which have multiple columns(4 in the following example) as null values. I have used the following code:
data[(data['relevent_experience'].isnull())&data['education_level'].isnull())&data['major_disciplne'].isnull())&data['relevent_experience'].isnull())]
This is a very complicated code. Is there a cleaner way to do the same thing?
Related
This question already has answers here:
Selecting multiple columns in a Pandas dataframe
(22 answers)
Closed last month.
I am an amateur user.
I watched many videos but I couldn't figure out this error.
How can I keep PERSON_WGHT, LOS, and IDC_DC_CD_1 as a columns for all rows that is 386816.
If you need to select multip0le columns from all the records then use df[[column_list]].
df_new = df[['PERSON_WGHT', 'LOS', 'IDC_DC_CD_1']]
This question already has answers here:
selecting from multi-index pandas
(7 answers)
Closed 1 year ago.
Check this image of dataframe
I've posted the picture of dataframe I am working with, I want to pull out data from specific times of a certain date
I've tried
stockdf.loc[("2015-01-01")].loc['09:17:00']
stockdf.loc[("2015-01-01","09:17:00"),:]
Both do not work.
Just try:
stockdf.loc[("2015-01-01", "09:17:00")]
If they're dates:
stockdf.loc[(pd.to_datetime("2015-01-01").date(), pd.to_datetime("09:17:00").time())]
This question already has answers here:
how to read certain columns from Excel using Pandas - Python
(6 answers)
Selecting multiple columns in a Pandas dataframe
(22 answers)
Closed 2 years ago.
I need to filter data of the columns according to string values, for example, I only need the columns that contain:
['CEMENTO MELON', 'G_CTRL_TE_DIEGO_DE_ALMAGRO','G_CTRL_EO_CANELA_2']
todos = []
for f in glob.glob('*.xlsx'):
#Here must go the code
todos.append(df)
I would greatly appreciate your help.
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How do I sum values in a column that match a given condition using pandas?
(3 answers)
Pandas counting and summing specific conditions
(4 answers)
Closed 5 years ago.
I am trying to convert fallowing SQL statement into pandas dataframe in python
SELECT sum(money) from df where sex='female'
I am unable to get this in pandas
Thanks in advance
df.loc[df.sex=='female','money'].sum()
This question already has answers here:
Filter pandas DataFrame by substring criteria
(17 answers)
Closed 7 years ago.
I have a DataFrame like this:
col1,col2
Sam,NL
Man,NL-USA
ho,CA-CN
And I would like to select the rows whose second column contains the word 'NL', which is something like SQL like command. Does anybody know about a similar command in Python Pandas?
The answer is here. Let df be your DataFrame.
df[df['col2'].str.contains('NL')]
This will select all the records that contain 'NL'.