I have two data frames. Examples:
df1:
A B C
5 7 6
8 1 1
1 0 7
3 4 9
5 7 4
9 2 0
df2:
A B C
3 2 1
6 5 7
9 7 9
1 1 2
6 4 5
0 8 6
Both data frames have same index.
What I want is , wherever df1's value is less than 5,
I want to update df2's value to 0, else keep it same.
I tried the following code:
df2[df1<5]=0
but when I am printing df2, its showing same values as original df2.
I know I am missing something really simple.
Please help me.
Thank you.
Related
I have a python data frame of weekly data like this :
Week Val
1 11
2 11
3 11
4 11
5 9
6 9
7 9
8 9
I would like create an output table like this:
Week 1 Week 2 Val
1 4 11
5 8 9
Apologies, I am quite new to python and its iterative tools. I am not sure how to solve this problem.
I tried to match using the previous row columns but I do not think how to go further:
df['Match'] = df['Val'].eq(df['Val'].shift(-1))
You want to groupby the consecutive blocks of Val. So you can use cumsum on the non-zero differences to get the block:
blocks = df['Val'].ne(df['Val'].shift(1)).cumsum()
(df.groupby(blocks, as_index=False)
.agg(Week1=('Week','min'), Week2=('Week','max'), Val=('Val', 'first'))
)
Or you can chain:
(df.groupby(df['Val'].ne(df['Val'].shift(1)).cumsum(), as_index=False)
.agg(Week1=('Week','min'), Week2=('Week','max'),Val=('Val', 'first'))
)
Output:
Week1 Week2 Val
0 1 4 11
1 5 8 9
I have multiple dataframes with a different number of rows and columns respectively.
example:
df1:
a b c d
0 1 5 6
8 9 8 7
and df2:
g h
9 8
4 5
6 7
I have to append both the dataframes without a change in their dimensions.
The desired output should be one dataframe Result_df as:
a b c d
0 1 5 6
8 9 8 7
g h
9 8
4 5
6 7
Can anyone please help me to append dataframes without change in their structure.
Thank you
I seem to run into some python or enumerate bugs that I am not quite sure how to fix it (See here for more details).
Long story short, I desire to see multiple data sets that has a column name of 0,4,6,8,10,12,14.
0 4 6 8 10 12
1 2 5 4 2 1
5 3 0 1 5 10
....
But my current data looks like the following
0 4 2 6 8 10 12
1 2 5 4 2 1
5 3 0 1 5 10
....
Therefore, I would like to add a code that keeps columns based on the index number (including only 0,4,6,8,10,12).
Is there a pandas function that can help with this?
A B ANSWER
1 1 1
3 3 3
1 2 1
2 4 2
4 4 4
5 5 5
6 6 6
i have used this function to get above answer "=IF(ISERROR(MATCH(A2:A8,$B$1:$B$8,0)),"",A2)"
but I need answer like this i have given below (suppose if you take value in A column "1"
Which is repeated only once in column B)
A B ANR
1 1 1
3 3 3
1 2 0
2 4 2
4 4 4
5 5 5
6 6 6
I've just wrapped your formula in a condition that returns 0 where the count of the A value from start to the current row is more than one:
=IF(COUNTIF(A$1:A2,A2)>1,0,IF(ISERROR(MATCH(A2:A8,$B$1:$B$8,0)),"",A2))
.
An alternative formula that gives the same results as above for the sample data provided but may (or may not) suit the additional requirements mentioned in a comment:
=IF(COUNTIF(A$2:A$10,A2)<=COUNTIF(B$2:B$10,A2),A2,IF(COUNTIF(A$2:A2,A2)>COUNTIF(B$2:B$10,A2),0,IF(COUNTIF(A$2:A$10,A2)>COUNTIF(B$2:B2,A2),A2,0)))
I am trying to fill data in MS Excel. I am given following pattern:
1 2
1
1
2 5
2 5
2
3
3 6
3
4
4
5 4
And I want my output in following format:
1 2
1 2
1 2
2 5
2 5
2 5
3 6
3 6
3 6
4
4
5 4
I tried using if(b2,b2,c1) in column 3. but that doesn't solve the problem for a=3 and a=4.
Any idea how to do this in Excel?
With sorting thus:
(the effect of which in this case is merely to move 6 up once cell) and a blank row above:
=IF(AND(A2<>A1,B2=""),"",IF(B2<>"",B2,C1))
In C2 and copied down should get the result you ask for from the data sample provided.