How to fill missing value based on other columns in Pandas dataframe?
$begingroup$
Suppose I have a 5*3 data frame in which third column contains missing value
1 2 3
4 5 NaN
7 8 9
3 2 NaN
5 6 NaN
I hope to generate value for missing value based rule that first product second column
1 2 3
4 5 20 <--4*5
7 8 9
3 2 6 <-- 3*2
5 6 30 <-- 5*6
How can I do it use data frame? Thanks.
How to add condition to calculate missing value like this?
if 1st % 2 == 0 then 3rd = 1st * 2nd
else 3rd = 1st + 2nd
1 2 3
4 5 20 <-- 4*5 because 4%2==0
7 8 9
3 2 5 <-- 3+2 because 3%2==1
5 6 11 <-- 5+6 because 5%2==1
pandas
asked Mar 22 '17 at 12:57
KyLKyL
149114
$endgroup$
add a comment |
$begingroup$
Suppose I have a 5*3 data frame in which third column contains missing value
1 2 3
4 5 NaN
7 8 9
3 2 NaN
5 6 NaN
I hope to generate value for missing value based rule that first product second column
1 2 3
4 5 20 <--4*5
7 8 9
3 2 6 <-- 3*2
5 6 30 <-- 5*6
How can I do it use data frame? Thanks.
How to add condition to calculate missing value like this?
if 1st % 2 == 0 then 3rd = 1st * 2nd
else 3rd = 1st + 2nd
1 2 3
4 5 20 <-- 4*5 because 4%2==0
7 8 9
3 2 5 <-- 3+2 because 3%2==1
5 6 11 <-- 5+6 because 5%2==1
pandas
asked Mar 22 '17 at 12:57
KyLKyL
149114
$endgroup$
$begingroup$
You can't do this because the size will not be equal
$endgroup$
– Mayur Dangar
Jul 7 '18 at 5:53
$begingroup$
Can you expand your answer? Why isn't it possible and what could he possibly do to solve problem?
$endgroup$
– Damian Melniczuk
Jul 7 '18 at 6:25
add a comment |
$begingroup$
Suppose I have a 5*3 data frame in which third column contains missing value
1 2 3
4 5 NaN
7 8 9
3 2 NaN
5 6 NaN
I hope to generate value for missing value based rule that first product second column
1 2 3
4 5 20 <--4*5
7 8 9
3 2 6 <-- 3*2
5 6 30 <-- 5*6
How can I do it use data frame? Thanks.
How to add condition to calculate missing value like this?
if 1st % 2 == 0 then 3rd = 1st * 2nd
else 3rd = 1st + 2nd
1 2 3
4 5 20 <-- 4*5 because 4%2==0
7 8 9
3 2 5 <-- 3+2 because 3%2==1
5 6 11 <-- 5+6 because 5%2==1
pandas
asked Mar 22 '17 at 12:57
KyLKyL
149114
$endgroup$
Suppose I have a 5*3 data frame in which third column contains missing value
1 2 3
4 5 NaN
7 8 9
3 2 NaN
5 6 NaN
I hope to generate value for missing value based rule that first product second column
1 2 3
4 5 20 <--4*5
7 8 9
3 2 6 <-- 3*2
5 6 30 <-- 5*6
How can I do it use data frame? Thanks.
How to add condition to calculate missing value like this?
if 1st % 2 == 0 then 3rd = 1st * 2nd
else 3rd = 1st + 2nd
1 2 3
4 5 20 <-- 4*5 because 4%2==0
7 8 9
3 2 5 <-- 3+2 because 3%2==1
5 6 11 <-- 5+6 because 5%2==1
pandas
pandas
asked Mar 22 '17 at 12:57
KyLKyL
149114
asked Mar 22 '17 at 12:57
KyLKyL
149114
edited Mar 22 '17 at 13:10
KyL
asked Mar 22 '17 at 12:57
KyLKyL
149114
asked Mar 22 '17 at 12:57
KyLKyL
149114
asked Mar 22 '17 at 12:57
KyLKyL
149114
149114
$begingroup$
You can't do this because the size will not be equal
$endgroup$
– Mayur Dangar
Jul 7 '18 at 5:53
$begingroup$
Can you expand your answer? Why isn't it possible and what could he possibly do to solve problem?
$endgroup$
– Damian Melniczuk
Jul 7 '18 at 6:25
add a comment |
$begingroup$
You can't do this because the size will not be equal
$endgroup$
– Mayur Dangar
Jul 7 '18 at 5:53
$begingroup$
Can you expand your answer? Why isn't it possible and what could he possibly do to solve problem?
$endgroup$
– Damian Melniczuk
Jul 7 '18 at 6:25
$begingroup$
You can't do this because the size will not be equal
$endgroup$
– Mayur Dangar
Jul 7 '18 at 5:53
$begingroup$
You can't do this because the size will not be equal
$endgroup$
– Mayur Dangar
Jul 7 '18 at 5:53
$begingroup$
Can you expand your answer? Why isn't it possible and what could he possibly do to solve problem?
$endgroup$
– Damian Melniczuk
Jul 7 '18 at 6:25
$begingroup$
Can you expand your answer? Why isn't it possible and what could he possibly do to solve problem?
$endgroup$
– Damian Melniczuk
Jul 7 '18 at 6:25
add a comment |
4 Answers
4
active
oldest
votes
$begingroup$
Assuming three columns of your dataframe is a, b and c. This is what you want:
df['c'] = df.apply(
lambda row: row['a']*row['b'] if np.isnan(row['c']) else row['c'],
axis=1
)
Full code:
df = pd.DataFrame(
np.array([[1, 2, 3], [4, 5, np.nan], [7, 8, 9], [3, 2, np.nan], [5, 6, np.nan]]),
columns=['a', 'b', 'c']
)
df['c'] = df.apply(
lambda row: row['a']*row['b'] if np.isnan(row['c']) else row['c'],
axis=1
)
answered Mar 22 '17 at 13:15
IcybladeIcyblade
2,5111333
$endgroup$
add a comment |
$begingroup$
Assuming that the three columns in your dataframe are a, b and c. Then you can do the required operation like this:
values = df['a'] * df['b']
df['c'] = values.where(df['c'] == np.nan, others=df['c'])
answered Mar 22 '17 at 13:45
NainNain
1,37951830
$endgroup$
1
$begingroup$
Ornp.where(pd.isnull(df.c), df.a * df.b, df.c)
$endgroup$
– Valentas
Apr 16 '18 at 7:18
add a comment |
$begingroup$
Another option:
df.loc[(pd.isnull(df.C), 'C'] = df.A * df.B
answered Jun 4 '18 at 19:24
VishalVishal
1634
$endgroup$
add a comment |
$begingroup$
hey even i have the same question . but what if the data i deal with is textual ? that is the condition is like "if 'ingredients' contains chicken then 'type'= non-veg"
answered 6 mins ago
user7389747user7389747
1
New contributor
user7389747 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
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4 Answers
4
active
oldest
votes
4 Answers
4
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
Assuming three columns of your dataframe is a, b and c. This is what you want:
df['c'] = df.apply(
lambda row: row['a']*row['b'] if np.isnan(row['c']) else row['c'],
axis=1
)
Full code:
df = pd.DataFrame(
np.array([[1, 2, 3], [4, 5, np.nan], [7, 8, 9], [3, 2, np.nan], [5, 6, np.nan]]),
columns=['a', 'b', 'c']
)
df['c'] = df.apply(
lambda row: row['a']*row['b'] if np.isnan(row['c']) else row['c'],
axis=1
)
answered Mar 22 '17 at 13:15
IcybladeIcyblade
2,5111333
$endgroup$
add a comment |
$begingroup$
Assuming three columns of your dataframe is a, b and c. This is what you want:
df['c'] = df.apply(
lambda row: row['a']*row['b'] if np.isnan(row['c']) else row['c'],
axis=1
)
Full code:
df = pd.DataFrame(
np.array([[1, 2, 3], [4, 5, np.nan], [7, 8, 9], [3, 2, np.nan], [5, 6, np.nan]]),
columns=['a', 'b', 'c']
)
df['c'] = df.apply(
lambda row: row['a']*row['b'] if np.isnan(row['c']) else row['c'],
axis=1
)
answered Mar 22 '17 at 13:15
IcybladeIcyblade
2,5111333
$endgroup$
add a comment |
$begingroup$
Assuming three columns of your dataframe is a, b and c. This is what you want:
df['c'] = df.apply(
lambda row: row['a']*row['b'] if np.isnan(row['c']) else row['c'],
axis=1
)
Full code:
df = pd.DataFrame(
np.array([[1, 2, 3], [4, 5, np.nan], [7, 8, 9], [3, 2, np.nan], [5, 6, np.nan]]),
columns=['a', 'b', 'c']
)
df['c'] = df.apply(
lambda row: row['a']*row['b'] if np.isnan(row['c']) else row['c'],
axis=1
)
answered Mar 22 '17 at 13:15
IcybladeIcyblade
2,5111333
$endgroup$
Assuming three columns of your dataframe is a, b and c. This is what you want:
df['c'] = df.apply(
lambda row: row['a']*row['b'] if np.isnan(row['c']) else row['c'],
axis=1
)
Full code:
df = pd.DataFrame(
np.array([[1, 2, 3], [4, 5, np.nan], [7, 8, 9], [3, 2, np.nan], [5, 6, np.nan]]),
columns=['a', 'b', 'c']
)
df['c'] = df.apply(
lambda row: row['a']*row['b'] if np.isnan(row['c']) else row['c'],
axis=1
)
answered Mar 22 '17 at 13:15
IcybladeIcyblade
2,5111333
answered Mar 22 '17 at 13:15
IcybladeIcyblade
2,5111333
answered Mar 22 '17 at 13:15
IcybladeIcyblade
2,5111333
answered Mar 22 '17 at 13:15
IcybladeIcyblade
2,5111333
2,5111333
add a comment |
add a comment |
$begingroup$
Assuming that the three columns in your dataframe are a, b and c. Then you can do the required operation like this:
values = df['a'] * df['b']
df['c'] = values.where(df['c'] == np.nan, others=df['c'])
answered Mar 22 '17 at 13:45
NainNain
1,37951830
$endgroup$
1
$begingroup$
Ornp.where(pd.isnull(df.c), df.a * df.b, df.c)
$endgroup$
– Valentas
Apr 16 '18 at 7:18
add a comment |
$begingroup$
Assuming that the three columns in your dataframe are a, b and c. Then you can do the required operation like this:
values = df['a'] * df['b']
df['c'] = values.where(df['c'] == np.nan, others=df['c'])
answered Mar 22 '17 at 13:45
NainNain
1,37951830
$endgroup$
1
$begingroup$
Ornp.where(pd.isnull(df.c), df.a * df.b, df.c)
$endgroup$
– Valentas
Apr 16 '18 at 7:18
add a comment |
$begingroup$
Assuming that the three columns in your dataframe are a, b and c. Then you can do the required operation like this:
values = df['a'] * df['b']
df['c'] = values.where(df['c'] == np.nan, others=df['c'])
answered Mar 22 '17 at 13:45
NainNain
1,37951830
$endgroup$
Assuming that the three columns in your dataframe are a, b and c. Then you can do the required operation like this:
values = df['a'] * df['b']
df['c'] = values.where(df['c'] == np.nan, others=df['c'])
answered Mar 22 '17 at 13:45
NainNain
1,37951830
answered Mar 22 '17 at 13:45
NainNain
1,37951830
answered Mar 22 '17 at 13:45
NainNain
1,37951830
answered Mar 22 '17 at 13:45
NainNain
1,37951830
1,37951830
1
$begingroup$
Ornp.where(pd.isnull(df.c), df.a * df.b, df.c)
$endgroup$
– Valentas
Apr 16 '18 at 7:18
add a comment |
1
$begingroup$
Ornp.where(pd.isnull(df.c), df.a * df.b, df.c)
$endgroup$
– Valentas
Apr 16 '18 at 7:18
1
1
$begingroup$
Or
np.where(pd.isnull(df.c), df.a * df.b, df.c)$endgroup$
– Valentas
Apr 16 '18 at 7:18
$begingroup$
Or
np.where(pd.isnull(df.c), df.a * df.b, df.c)$endgroup$
– Valentas
Apr 16 '18 at 7:18
add a comment |
$begingroup$
Another option:
df.loc[(pd.isnull(df.C), 'C'] = df.A * df.B
answered Jun 4 '18 at 19:24
VishalVishal
1634
$endgroup$
add a comment |
$begingroup$
Another option:
df.loc[(pd.isnull(df.C), 'C'] = df.A * df.B
answered Jun 4 '18 at 19:24
VishalVishal
1634
$endgroup$
add a comment |
$begingroup$
Another option:
df.loc[(pd.isnull(df.C), 'C'] = df.A * df.B
answered Jun 4 '18 at 19:24
VishalVishal
1634
$endgroup$
Another option:
df.loc[(pd.isnull(df.C), 'C'] = df.A * df.B
answered Jun 4 '18 at 19:24
VishalVishal
1634
answered Jun 4 '18 at 19:24
VishalVishal
1634
answered Jun 4 '18 at 19:24
VishalVishal
1634
answered Jun 4 '18 at 19:24
VishalVishal
1634
1634
add a comment |
add a comment |
$begingroup$
hey even i have the same question . but what if the data i deal with is textual ? that is the condition is like "if 'ingredients' contains chicken then 'type'= non-veg"
answered 6 mins ago
user7389747user7389747
1
New contributor
user7389747 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
hey even i have the same question . but what if the data i deal with is textual ? that is the condition is like "if 'ingredients' contains chicken then 'type'= non-veg"
answered 6 mins ago
user7389747user7389747
1
New contributor
user7389747 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
hey even i have the same question . but what if the data i deal with is textual ? that is the condition is like "if 'ingredients' contains chicken then 'type'= non-veg"
answered 6 mins ago
user7389747user7389747
1
New contributor
user7389747 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
hey even i have the same question . but what if the data i deal with is textual ? that is the condition is like "if 'ingredients' contains chicken then 'type'= non-veg"
answered 6 mins ago
user7389747user7389747
1
New contributor
user7389747 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
answered 6 mins ago
user7389747user7389747
1
New contributor
user7389747 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
answered 6 mins ago
user7389747user7389747
1
answered 6 mins ago
user7389747user7389747
1
1
New contributor
user7389747 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
user7389747 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
user7389747 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
add a comment |
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$begingroup$
You can't do this because the size will not be equal
$endgroup$
– Mayur Dangar
Jul 7 '18 at 5:53
$begingroup$
Can you expand your answer? Why isn't it possible and what could he possibly do to solve problem?
$endgroup$
– Damian Melniczuk
Jul 7 '18 at 6:25