pandas reading data from column in as float or int and not str despite dtype setting
i have an issue with pandas (0.23.4) on python 3.7 where the data is being read in as scientific notation instead of just a string despite setting the dtype setting. Here is an example of the data that is being read in
-------------------
codes
-------------------
001234544
00023455
123456789
A1253532
780E9000
00678E10
The problem comes with lines 5 and 6 of the above because they contain, i think, 'E' characters and they are being turned into scientific notation.
My reader is setup as follows.
accounts = pd.read_excel('gym_accounts.xlsx', sheet_name='Sheet1', dtype=str)
despite that dtype=str setting, it appears that pandas using something called ... a "sniffer" that detects the data type automatically and its being changed back to what I assume is float or int, and then changing it to scientific notation. One suggestion in another thread says to use something called a converter statement within the read_csv like the following
pd.read_csv('my.csv', converters = {i: str for i in range(0, 100)})
I am curious if this is a possible solution to my problem, but also i have no idea how long that range should be as it changes often. Is there any way to query the length of the column and feed that as a variable into that range call?
I looks like i can do something like len(accounts.index) ... but i cant do this till after the reader has read the file so something like this below doesnt work
accounts = pd.read_excel('gym_accounts.xlsx', sheet_name='Sheet1', converters = {i: str for i in range(0, gym_length)}))
gym_length = len(accounts.index)
the length check is after the .. i guess you call it ... data reader, so it doesnt work obviously.
python-3.x pandas csv
asked Nov 26 '18 at 0:44
OscalationOscalation
23318
add a comment |
i have an issue with pandas (0.23.4) on python 3.7 where the data is being read in as scientific notation instead of just a string despite setting the dtype setting. Here is an example of the data that is being read in
-------------------
codes
-------------------
001234544
00023455
123456789
A1253532
780E9000
00678E10
The problem comes with lines 5 and 6 of the above because they contain, i think, 'E' characters and they are being turned into scientific notation.
My reader is setup as follows.
accounts = pd.read_excel('gym_accounts.xlsx', sheet_name='Sheet1', dtype=str)
despite that dtype=str setting, it appears that pandas using something called ... a "sniffer" that detects the data type automatically and its being changed back to what I assume is float or int, and then changing it to scientific notation. One suggestion in another thread says to use something called a converter statement within the read_csv like the following
pd.read_csv('my.csv', converters = {i: str for i in range(0, 100)})
I am curious if this is a possible solution to my problem, but also i have no idea how long that range should be as it changes often. Is there any way to query the length of the column and feed that as a variable into that range call?
I looks like i can do something like len(accounts.index) ... but i cant do this till after the reader has read the file so something like this below doesnt work
accounts = pd.read_excel('gym_accounts.xlsx', sheet_name='Sheet1', converters = {i: str for i in range(0, gym_length)}))
gym_length = len(accounts.index)
the length check is after the .. i guess you call it ... data reader, so it doesnt work obviously.
python-3.x pandas csv
asked Nov 26 '18 at 0:44
OscalationOscalation
23318
I am afraid this is not reproducible without example file. Copying your example data into libreoffice and saving as gym_accounts.xlsx and then using your code to read it into pandas does not cut it. The data is read as str in that case as expected.
– 0range
Nov 29 '18 at 22:25
add a comment |
i have an issue with pandas (0.23.4) on python 3.7 where the data is being read in as scientific notation instead of just a string despite setting the dtype setting. Here is an example of the data that is being read in
-------------------
codes
-------------------
001234544
00023455
123456789
A1253532
780E9000
00678E10
The problem comes with lines 5 and 6 of the above because they contain, i think, 'E' characters and they are being turned into scientific notation.
My reader is setup as follows.
accounts = pd.read_excel('gym_accounts.xlsx', sheet_name='Sheet1', dtype=str)
despite that dtype=str setting, it appears that pandas using something called ... a "sniffer" that detects the data type automatically and its being changed back to what I assume is float or int, and then changing it to scientific notation. One suggestion in another thread says to use something called a converter statement within the read_csv like the following
pd.read_csv('my.csv', converters = {i: str for i in range(0, 100)})
I am curious if this is a possible solution to my problem, but also i have no idea how long that range should be as it changes often. Is there any way to query the length of the column and feed that as a variable into that range call?
I looks like i can do something like len(accounts.index) ... but i cant do this till after the reader has read the file so something like this below doesnt work
accounts = pd.read_excel('gym_accounts.xlsx', sheet_name='Sheet1', converters = {i: str for i in range(0, gym_length)}))
gym_length = len(accounts.index)
the length check is after the .. i guess you call it ... data reader, so it doesnt work obviously.
python-3.x pandas csv
asked Nov 26 '18 at 0:44
OscalationOscalation
23318
i have an issue with pandas (0.23.4) on python 3.7 where the data is being read in as scientific notation instead of just a string despite setting the dtype setting. Here is an example of the data that is being read in
-------------------
codes
-------------------
001234544
00023455
123456789
A1253532
780E9000
00678E10
The problem comes with lines 5 and 6 of the above because they contain, i think, 'E' characters and they are being turned into scientific notation.
My reader is setup as follows.
accounts = pd.read_excel('gym_accounts.xlsx', sheet_name='Sheet1', dtype=str)
despite that dtype=str setting, it appears that pandas using something called ... a "sniffer" that detects the data type automatically and its being changed back to what I assume is float or int, and then changing it to scientific notation. One suggestion in another thread says to use something called a converter statement within the read_csv like the following
pd.read_csv('my.csv', converters = {i: str for i in range(0, 100)})
I am curious if this is a possible solution to my problem, but also i have no idea how long that range should be as it changes often. Is there any way to query the length of the column and feed that as a variable into that range call?
I looks like i can do something like len(accounts.index) ... but i cant do this till after the reader has read the file so something like this below doesnt work
accounts = pd.read_excel('gym_accounts.xlsx', sheet_name='Sheet1', converters = {i: str for i in range(0, gym_length)}))
gym_length = len(accounts.index)
the length check is after the .. i guess you call it ... data reader, so it doesnt work obviously.
python-3.x pandas csv
python-3.x pandas csv
asked Nov 26 '18 at 0:44
OscalationOscalation
23318
asked Nov 26 '18 at 0:44
OscalationOscalation
23318
edited Nov 26 '18 at 1:19
Oscalation
asked Nov 26 '18 at 0:44
OscalationOscalation
23318
asked Nov 26 '18 at 0:44
OscalationOscalation
23318
asked Nov 26 '18 at 0:44
OscalationOscalation
23318
23318
I am afraid this is not reproducible without example file. Copying your example data into libreoffice and saving as gym_accounts.xlsx and then using your code to read it into pandas does not cut it. The data is read as str in that case as expected.
– 0range
Nov 29 '18 at 22:25
add a comment |
I am afraid this is not reproducible without example file. Copying your example data into libreoffice and saving as gym_accounts.xlsx and then using your code to read it into pandas does not cut it. The data is read as str in that case as expected.
– 0range
Nov 29 '18 at 22:25
I am afraid this is not reproducible without example file. Copying your example data into libreoffice and saving as gym_accounts.xlsx and then using your code to read it into pandas does not cut it. The data is read as str in that case as expected.
– 0range
Nov 29 '18 at 22:25
I am afraid this is not reproducible without example file. Copying your example data into libreoffice and saving as gym_accounts.xlsx and then using your code to read it into pandas does not cut it. The data is read as str in that case as expected.
– 0range
Nov 29 '18 at 22:25
add a comment |
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I am afraid this is not reproducible without example file. Copying your example data into libreoffice and saving as gym_accounts.xlsx and then using your code to read it into pandas does not cut it. The data is read as str in that case as expected.
– 0range
Nov 29 '18 at 22:25