Update Values in a dataframe by merging
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I have got two dataframes; the first is an empty one, with dates as rows and Products as columns. The second contains the value of the inventory, for a specific item.
The rows and the columns that are in the latter appear in the first one as well:
print(inventory_df)
dt_op Prod_1 Prod_2 ... Prod_n
10/09/18 0 0 0
11/09/18 0 0 0
12/09/18 0 0 0
...
print(final_inspect)
dt_op Prod_1
10/09/18 10
11/09/18 2
12/09/18 5
I would like to update the values in inventory_df, obtaining the following dataframe:
print(updated_df)
dt_op Prod_1 Prod_2 ... Prod_n
10/09/18 10 0 0
11/09/18 2 0 0
12/09/18 5 0 0
...
I tried with a redoundant method, concatenating and then removing duplicates, but when I use pd.concat it raises:
TypeError: cannot concatenate object of type "<class 'list'>"; only pd.Series, pd.DataFrame, and pd.Panel (deprecated) objs are valid
How can I merge the first two frames to create the updated one?
N.B. The size of updated_df has to be the same as inventory_df, and nrows of final_inspect are less than nrows of inventory_df.
python pandas merge
asked Nov 19 at 12:31
Alessandro Ceccarelli
216210
add a comment |
up vote
0
down vote
favorite
I have got two dataframes; the first is an empty one, with dates as rows and Products as columns. The second contains the value of the inventory, for a specific item.
The rows and the columns that are in the latter appear in the first one as well:
print(inventory_df)
dt_op Prod_1 Prod_2 ... Prod_n
10/09/18 0 0 0
11/09/18 0 0 0
12/09/18 0 0 0
...
print(final_inspect)
dt_op Prod_1
10/09/18 10
11/09/18 2
12/09/18 5
I would like to update the values in inventory_df, obtaining the following dataframe:
print(updated_df)
dt_op Prod_1 Prod_2 ... Prod_n
10/09/18 10 0 0
11/09/18 2 0 0
12/09/18 5 0 0
...
I tried with a redoundant method, concatenating and then removing duplicates, but when I use pd.concat it raises:
TypeError: cannot concatenate object of type "<class 'list'>"; only pd.Series, pd.DataFrame, and pd.Panel (deprecated) objs are valid
How can I merge the first two frames to create the updated one?
N.B. The size of updated_df has to be the same as inventory_df, and nrows of final_inspect are less than nrows of inventory_df.
python pandas merge
asked Nov 19 at 12:31
Alessandro Ceccarelli
216210
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I have got two dataframes; the first is an empty one, with dates as rows and Products as columns. The second contains the value of the inventory, for a specific item.
The rows and the columns that are in the latter appear in the first one as well:
print(inventory_df)
dt_op Prod_1 Prod_2 ... Prod_n
10/09/18 0 0 0
11/09/18 0 0 0
12/09/18 0 0 0
...
print(final_inspect)
dt_op Prod_1
10/09/18 10
11/09/18 2
12/09/18 5
I would like to update the values in inventory_df, obtaining the following dataframe:
print(updated_df)
dt_op Prod_1 Prod_2 ... Prod_n
10/09/18 10 0 0
11/09/18 2 0 0
12/09/18 5 0 0
...
I tried with a redoundant method, concatenating and then removing duplicates, but when I use pd.concat it raises:
TypeError: cannot concatenate object of type "<class 'list'>"; only pd.Series, pd.DataFrame, and pd.Panel (deprecated) objs are valid
How can I merge the first two frames to create the updated one?
N.B. The size of updated_df has to be the same as inventory_df, and nrows of final_inspect are less than nrows of inventory_df.
python pandas merge
asked Nov 19 at 12:31
Alessandro Ceccarelli
216210
I have got two dataframes; the first is an empty one, with dates as rows and Products as columns. The second contains the value of the inventory, for a specific item.
The rows and the columns that are in the latter appear in the first one as well:
print(inventory_df)
dt_op Prod_1 Prod_2 ... Prod_n
10/09/18 0 0 0
11/09/18 0 0 0
12/09/18 0 0 0
...
print(final_inspect)
dt_op Prod_1
10/09/18 10
11/09/18 2
12/09/18 5
I would like to update the values in inventory_df, obtaining the following dataframe:
print(updated_df)
dt_op Prod_1 Prod_2 ... Prod_n
10/09/18 10 0 0
11/09/18 2 0 0
12/09/18 5 0 0
...
I tried with a redoundant method, concatenating and then removing duplicates, but when I use pd.concat it raises:
TypeError: cannot concatenate object of type "<class 'list'>"; only pd.Series, pd.DataFrame, and pd.Panel (deprecated) objs are valid
How can I merge the first two frames to create the updated one?
N.B. The size of updated_df has to be the same as inventory_df, and nrows of final_inspect are less than nrows of inventory_df.
python pandas merge
python pandas merge
asked Nov 19 at 12:31
Alessandro Ceccarelli
216210
asked Nov 19 at 12:31
Alessandro Ceccarelli
216210
edited Nov 19 at 14:25
asked Nov 19 at 12:31
Alessandro Ceccarelli
216210
asked Nov 19 at 12:31
Alessandro Ceccarelli
216210
asked Nov 19 at 12:31
Alessandro Ceccarelli
216210
216210
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
up vote
0
down vote
accepted
Use df.update()-
inventory_df.update(final_inspect)
Output
dt_op Prod_1 Prod_2
0 10/09/18 10 0
1 11/09/18 2 0
2 12/09/18 5 0
This by default implements a join='left, wherein you can take care of non-matching na values as you wish
answered Nov 19 at 12:38
Vivek Kalyanarangan
4,3681726
It does not seem to produce a result; the function should be the right one but it does not update the dataframe. What could be the reasons?
– Alessandro Ceccarelli
Nov 19 at 14:22
@AlessandroCeccarelli It updates thedfinplace, i.e. theinventory_dfis updated directly
– Vivek Kalyanarangan
Nov 19 at 14:25
I know, but at the moment, whenever I run "inventory_df.update(final_inspect)", inventory_df is not changed, even though there are not missing values, and the columns are the same.
– Alessandro Ceccarelli
Nov 19 at 14:39
Thats funny, not sure what might be going wrong, working fine for me :(
– Vivek Kalyanarangan
Nov 19 at 14:43
It does not work on my dataframe, nonetheless it does work with some other examples I've made for testing purposes.
– Alessandro Ceccarelli
Nov 19 at 16:12
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
Use df.update()-
inventory_df.update(final_inspect)
Output
dt_op Prod_1 Prod_2
0 10/09/18 10 0
1 11/09/18 2 0
2 12/09/18 5 0
This by default implements a join='left, wherein you can take care of non-matching na values as you wish
answered Nov 19 at 12:38
Vivek Kalyanarangan
4,3681726
It does not seem to produce a result; the function should be the right one but it does not update the dataframe. What could be the reasons?
– Alessandro Ceccarelli
Nov 19 at 14:22
@AlessandroCeccarelli It updates thedfinplace, i.e. theinventory_dfis updated directly
– Vivek Kalyanarangan
Nov 19 at 14:25
I know, but at the moment, whenever I run "inventory_df.update(final_inspect)", inventory_df is not changed, even though there are not missing values, and the columns are the same.
– Alessandro Ceccarelli
Nov 19 at 14:39
Thats funny, not sure what might be going wrong, working fine for me :(
– Vivek Kalyanarangan
Nov 19 at 14:43
It does not work on my dataframe, nonetheless it does work with some other examples I've made for testing purposes.
– Alessandro Ceccarelli
Nov 19 at 16:12
add a comment |
up vote
0
down vote
accepted
Use df.update()-
inventory_df.update(final_inspect)
Output
dt_op Prod_1 Prod_2
0 10/09/18 10 0
1 11/09/18 2 0
2 12/09/18 5 0
This by default implements a join='left, wherein you can take care of non-matching na values as you wish
answered Nov 19 at 12:38
Vivek Kalyanarangan
4,3681726
It does not seem to produce a result; the function should be the right one but it does not update the dataframe. What could be the reasons?
– Alessandro Ceccarelli
Nov 19 at 14:22
@AlessandroCeccarelli It updates thedfinplace, i.e. theinventory_dfis updated directly
– Vivek Kalyanarangan
Nov 19 at 14:25
I know, but at the moment, whenever I run "inventory_df.update(final_inspect)", inventory_df is not changed, even though there are not missing values, and the columns are the same.
– Alessandro Ceccarelli
Nov 19 at 14:39
Thats funny, not sure what might be going wrong, working fine for me :(
– Vivek Kalyanarangan
Nov 19 at 14:43
It does not work on my dataframe, nonetheless it does work with some other examples I've made for testing purposes.
– Alessandro Ceccarelli
Nov 19 at 16:12
add a comment |
up vote
0
down vote
accepted
up vote
0
down vote
accepted
Use df.update()-
inventory_df.update(final_inspect)
Output
dt_op Prod_1 Prod_2
0 10/09/18 10 0
1 11/09/18 2 0
2 12/09/18 5 0
This by default implements a join='left, wherein you can take care of non-matching na values as you wish
answered Nov 19 at 12:38
Vivek Kalyanarangan
4,3681726
Use df.update()-
inventory_df.update(final_inspect)
Output
dt_op Prod_1 Prod_2
0 10/09/18 10 0
1 11/09/18 2 0
2 12/09/18 5 0
This by default implements a join='left, wherein you can take care of non-matching na values as you wish
answered Nov 19 at 12:38
Vivek Kalyanarangan
4,3681726
answered Nov 19 at 12:38
Vivek Kalyanarangan
4,3681726
answered Nov 19 at 12:38
Vivek Kalyanarangan
4,3681726
answered Nov 19 at 12:38
Vivek Kalyanarangan
4,3681726
4,3681726
It does not seem to produce a result; the function should be the right one but it does not update the dataframe. What could be the reasons?
– Alessandro Ceccarelli
Nov 19 at 14:22
@AlessandroCeccarelli It updates thedfinplace, i.e. theinventory_dfis updated directly
– Vivek Kalyanarangan
Nov 19 at 14:25
I know, but at the moment, whenever I run "inventory_df.update(final_inspect)", inventory_df is not changed, even though there are not missing values, and the columns are the same.
– Alessandro Ceccarelli
Nov 19 at 14:39
Thats funny, not sure what might be going wrong, working fine for me :(
– Vivek Kalyanarangan
Nov 19 at 14:43
It does not work on my dataframe, nonetheless it does work with some other examples I've made for testing purposes.
– Alessandro Ceccarelli
Nov 19 at 16:12
add a comment |
It does not seem to produce a result; the function should be the right one but it does not update the dataframe. What could be the reasons?
– Alessandro Ceccarelli
Nov 19 at 14:22
@AlessandroCeccarelli It updates thedfinplace, i.e. theinventory_dfis updated directly
– Vivek Kalyanarangan
Nov 19 at 14:25
I know, but at the moment, whenever I run "inventory_df.update(final_inspect)", inventory_df is not changed, even though there are not missing values, and the columns are the same.
– Alessandro Ceccarelli
Nov 19 at 14:39
Thats funny, not sure what might be going wrong, working fine for me :(
– Vivek Kalyanarangan
Nov 19 at 14:43
It does not work on my dataframe, nonetheless it does work with some other examples I've made for testing purposes.
– Alessandro Ceccarelli
Nov 19 at 16:12
It does not seem to produce a result; the function should be the right one but it does not update the dataframe. What could be the reasons?
– Alessandro Ceccarelli
Nov 19 at 14:22
It does not seem to produce a result; the function should be the right one but it does not update the dataframe. What could be the reasons?
– Alessandro Ceccarelli
Nov 19 at 14:22
@AlessandroCeccarelli It updates the
df inplace, i.e. the inventory_df is updated directly– Vivek Kalyanarangan
Nov 19 at 14:25
@AlessandroCeccarelli It updates the
df inplace, i.e. the inventory_df is updated directly– Vivek Kalyanarangan
Nov 19 at 14:25
I know, but at the moment, whenever I run "inventory_df.update(final_inspect)", inventory_df is not changed, even though there are not missing values, and the columns are the same.
– Alessandro Ceccarelli
Nov 19 at 14:39
I know, but at the moment, whenever I run "inventory_df.update(final_inspect)", inventory_df is not changed, even though there are not missing values, and the columns are the same.
– Alessandro Ceccarelli
Nov 19 at 14:39
Thats funny, not sure what might be going wrong, working fine for me :(
– Vivek Kalyanarangan
Nov 19 at 14:43
Thats funny, not sure what might be going wrong, working fine for me :(
– Vivek Kalyanarangan
Nov 19 at 14:43
It does not work on my dataframe, nonetheless it does work with some other examples I've made for testing purposes.
– Alessandro Ceccarelli
Nov 19 at 16:12
It does not work on my dataframe, nonetheless it does work with some other examples I've made for testing purposes.
– Alessandro Ceccarelli
Nov 19 at 16:12
add a comment |
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