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Write python code to find the total number of null values on the excel file without using isnull function ( you should use loop statement)
Using for statement in dataframes is not a good practice. If you're doing only for challenge, this could help:
data = pd.read_excel('data.xlsx')
data.fillna(False, inplace=True)
amount_nan = 0
for column in data:
for value in data[column]:
if not value:
amount_nan = amount_nan + 1
print(amount_nan)
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I have this:
a = ['a','b','c','d','e','f']
And I want to make it into this:
a = ['ab','cd','ef']
I tried this:
for i in range(len(a)):
if round(i/2) > len(a):
break
c = (a[(i*2)-1])+(a[i*2])
c_list.append(c)
But it didn't work, and I felt it wasn't the best way to approach it.
def pair_up(a):
return [a[i]+a[i+1] for i in range(0,len(a),2)]
print(pair_up(a))
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I'd like to drop a '.' from a column name using regex, and want the code to be applied to many column names that end in '.', so that each pair of like-named columns can be merged into one.
For example, the column names 'Fund' and 'Fund.' are different and have different values, but should become just 'Fund'.
What would be the best regex to use for this?
Try this:
df = pd.DataFrame([1], columns=['Fund.'])
df.columns = df.columns.str.replace('.','')
Output:
print(df.columns)
Index(['Fund'], dtype='object')
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I tried to append these values in the list but it appends only else part.
I want to store these values i printed in a list. How can i achieve this??
for i in d["Cabin new"]:
if i=="nan":
print ("na")
else:
print (i[1:])
Append in both places:
res = []
for i in d["Cabin new"]:
if i=="nan":
res.append('na')
else:
res.append(i[1:])
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When working with pandas, I often use name based column indexing. E.g:
df = pd.DataFrame({"abc":[1,2], "bde":[3,4], "mde":[3,4]})
df[["mde","bde"]]
As I have longer column names it because easy for me to create a typo in the column names since they are strings and no code completion. It'd be great if I could do something like:
df.SelectColumnsByObjectAttributeNotString([df.mde, df.bde])
IIUC, you can use name attribute.
df = pd.DataFrame({"a":[1,2], "b":[3,4]})
columns = [df.a.name, df.b.name]
columns
['a', 'b']
I think you may be looking for:
df.columns.values.tolist()
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Please help.
I have data in text file with 2 long columns tab spaced
I have to extract first and second columns separately
Can it be done with Python ?
If you need the columns as two separate lists:
first_column = []
second_column = []
data_file = open('your_file.txt')
for line in data_file.readlines():
first_column.append(line.split('\t')[0])
second_column.append(line.split('\t')[1])
data_file.close()