I am reading output of dataframe.isnull().sum() but it shows as collapsed. How can I expand the cell so that i can see all columsn NAs count. There are total 81 columsn but i am seeing only few
Try add this in your code :
import pandas as pd
pd.set_option('display.max_rows', None)
You can also print the entire data frame as well:
print(df.to_string())
Related
Hello, as you see here i have a csv file. The problem is first column (leftmost) does not begin with 1 but it is like the column "gene". How can i fix it?
I want that starts with 1 and go to end of the list.
Did you do this?
import pandas as pd
pd.read_csv('your_file.csv', index_col='Gene')
Just remove index_col and it should, by default, create a new index column.
I am stuck here, but I it's a two part question. Looking at the output of .describe(include = 'all'), not all columns are showing; how do I get all columns to show?
This is a common problem that I have all of the time with Spyder, how to have all columns to show in Console. Any help is appreciated.
import matplotlib.pyplot as plt
import pandas as pd
import scipy.stats as stats
import seaborn as sns
mydata = pd.read_csv("E:\ho11.csv")
mydata.head()
print(mydata.describe(include="all", exclude = None))
mydata.info()
OUTPUT:
code output
Solution
You could use either of the following methods:
Method-1:
source
pd.options.display.max_columns = None
Method-2:
source
pd.set_option('display.max_columns', None)
# to reset this
pd.reset_option('display.max_columns')
Method-3:
source
# assuming df is your dataframe
pd.set_option('display.max_columns', df.columns.size)
# to reset this
pd.reset_option('display.max_columns')
Method-4:
source
# assuming df is your dataframe
pd.set_option('max_columns', df.columns.size)
# to reset this
pd.reset_option('max_columns')
To not wrap the output into multiple lines do this
source
pd.set_option('display.expand_frame_repr', False)
References
I will recommend you to explore the following resources for more details and examples.
How to show all of columns name on pandas dataframe?
How do I expand the output display to see more columns of a pandas DataFrame?
How to show all columns / rows of a Pandas Dataframe?
Since you are using Spyder the easiest thing to do would be:
myview = mydata.describe()
Then you can inspect 'myview' in the variable explorer.
Using pd.set_option listed column names in the console truncated in the middle with three dots.
To print a full list of the column names from a dataframe to the console in Spyder:
list(df.columns)
I have a column in a dataframe (df) in pandas called "9-7". When I use df.to_csv('df.csv') to save the dataframe, the title of the column is changed to 7-Sep. It means the date of the 7 of September. However, I need the title of "9-7".
This has to do with excel's interpretation of data. A csv-file is nothing more than a table in string format.
If you are going to continue in excel you could use to.excel() function:
import pandas as pd
pd.DataFrame({'9-7':[1]}).to_csv('test.csv',index=False) # This will not work
pd.DataFrame({'9-7':[1]}).to_excel('test.xlsx',index=False) # This will
When I use style to format a pandas dataframe in a Jupyter notebook, the name of the columns (df.columns.name) is not displayed.
How can I fix this?
Set up:
import pandas as pd
from IPython.display import HTML, display
df = pd.DataFrame([[1,2,3],[4,5,6],[7,8,9]], columns = [-1,0,1], index=[-1,0,1])
df.index.name = 'A'
df.columns.name = 'B'
This is how the data look like:
display(df) # Has name of columns 'B'
Now, I want to add percentage formatting to all columns:
display(df.style.format("{:.1%}"))
but I have lost the name of columns!
I try your code, not find your problems, I get this:
I think you update your pandas or jupyter version will fix it.
If I use DataFrame.set_index, I get this result:
import pandas as pd
df = pd.DataFrame([['foo',1,3.0],['bar',2,2.9],
['baz',4,2.85],['quux',3,2.82]],
columns=['name','order','gpa'])
df.set_index('name')
Note the unnecessary row... I know it does this because it reserves the upper left cell for the column title, but I don't care about it, and it makes my table look somewhat unprofessional if I use it in a presentation.
If I don't use DataFrame.set_index, the extra row is gone, but I get numeric row indices, which I don't want:
If I use to_html(index=False) then I solve those problems, but the first column isn't bold:
import pandas as pd
from IPython.display import HTML
df = pd.DataFrame([['foo',1,3.0],['bar',2,2.9],
['baz',4,2.85],['quux',3,2.82]],
columns=['name','order','gpa'])
HTML(df.to_html(index=False))
If I want to control styling to make the names boldface, I guess I could use the new Styler API via HTML(df.style.do_something_here().render()) but I can't figure out how to achieve the index=False functionality.
What's a hacker to do? (besides construct the HTML myself)
I poked around in the source for Styler and figured it out; if you set df.index.names = [None] then this suppresses the "extra" row (along with the column header that I don't really care about):
import pandas as pd
df = pd.DataFrame([['foo',1,3.0],['bar',2,2.9],
['baz',4,2.85],['quux',3,2.82]],
columns=['name','order','gpa'])
df = df.set_index('name')
df.index.names = [None]
df
These days pandas actually has a keyword for this:
df.to_html(index_names=False)
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_html.html