Python: Combining Two Rows with Pandas read_excel The 2019 Stack Overflow Developer Survey Results Are InExcel's SUMIFS implemented using PANDAS, the Python Data Analysis LibrarySQL GROUPING SETS in Python using PandasPython Pandas Apply with a Lambda FunctionSlow code pandas 8 million rowsDropping rows from a PANDAS dataframe where some of the columns have value 0Munging select rows in CSV files using PandasMatching rows between two dataframesGrouped by First Two Digits of Account_ID of ~240 million rows of Pandas DFSubtable timestamps in python pandasCalculating time deltas between rows in a Pandas dataframe
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Python: Combining Two Rows with Pandas read_excel
The 2019 Stack Overflow Developer Survey Results Are InExcel's SUMIFS implemented using PANDAS, the Python Data Analysis LibrarySQL GROUPING SETS in Python using PandasPython Pandas Apply with a Lambda FunctionSlow code pandas 8 million rowsDropping rows from a PANDAS dataframe where some of the columns have value 0Munging select rows in CSV files using PandasMatching rows between two dataframesGrouped by First Two Digits of Account_ID of ~240 million rows of Pandas DFSubtable timestamps in python pandasCalculating time deltas between rows in a Pandas dataframe
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$begingroup$
I am reading an Excel file using Pandas and I feel like there has to be a better way to handle the way I create column names. This is something like the Excel file I'm reading:
1 2 # '1' is merged in the two cells above 'a'and 'b'
Date a b c d # likewise for '2'. As opposed to 'centered across selection'
1 1-Jan-19 100 200 300 400
2 1-Feb-19 101 201 301 401
3 1-Mar-19 102 202 302 402
I want my to merge the 'a','b','c',and'd' columns with the '1'and '2' above them, so I'm doing the following to get my headers the way that I want:
import pandas as pd
import json
xls = pd.ExcelFile(r'C:Path_toExcel_Pandas_Connector_Test.xls')
df = pd.read_excel(xls, 'Sheet1', header=[1]) # uses the abcd row as column names
# I only want the most recent day of data so I do the following
json_str = df[df.Date == df['Date'].max()].to_json(orient='records',date_format='iso')
dat_data = json.loads(json_str)[0]
def clean_json():
global dat_data
dat_data['1a'] = dat_data.pop('a')
dat_data['1b'] = dat_data.pop('b')
dat_data['2c'] = dat_data.pop('c')
dat_data['2d'] = dat_data.pop('d')
clean_json()
print(json.dumps(dat_data,indent=4))
My desired output is:
"Date": "2019-03-01T00:00:00.000Z",
"1a": 102,
"1b": 202,
"2c": 302,
"2d": 402
This works as written, but is there a Pandas built-in that I could have used to do the same thing instead of the clean_json function?
python excel pandas
asked 59 mins ago
VirgilioVirgilio
62
New contributor
Virgilio 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 |
$begingroup$
I am reading an Excel file using Pandas and I feel like there has to be a better way to handle the way I create column names. This is something like the Excel file I'm reading:
1 2 # '1' is merged in the two cells above 'a'and 'b'
Date a b c d # likewise for '2'. As opposed to 'centered across selection'
1 1-Jan-19 100 200 300 400
2 1-Feb-19 101 201 301 401
3 1-Mar-19 102 202 302 402
I want my to merge the 'a','b','c',and'd' columns with the '1'and '2' above them, so I'm doing the following to get my headers the way that I want:
import pandas as pd
import json
xls = pd.ExcelFile(r'C:Path_toExcel_Pandas_Connector_Test.xls')
df = pd.read_excel(xls, 'Sheet1', header=[1]) # uses the abcd row as column names
# I only want the most recent day of data so I do the following
json_str = df[df.Date == df['Date'].max()].to_json(orient='records',date_format='iso')
dat_data = json.loads(json_str)[0]
def clean_json():
global dat_data
dat_data['1a'] = dat_data.pop('a')
dat_data['1b'] = dat_data.pop('b')
dat_data['2c'] = dat_data.pop('c')
dat_data['2d'] = dat_data.pop('d')
clean_json()
print(json.dumps(dat_data,indent=4))
My desired output is:
"Date": "2019-03-01T00:00:00.000Z",
"1a": 102,
"1b": 202,
"2c": 302,
"2d": 402
This works as written, but is there a Pandas built-in that I could have used to do the same thing instead of the clean_json function?
python excel pandas
asked 59 mins ago
VirgilioVirgilio
62
New contributor
Virgilio 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 |
$begingroup$
I am reading an Excel file using Pandas and I feel like there has to be a better way to handle the way I create column names. This is something like the Excel file I'm reading:
1 2 # '1' is merged in the two cells above 'a'and 'b'
Date a b c d # likewise for '2'. As opposed to 'centered across selection'
1 1-Jan-19 100 200 300 400
2 1-Feb-19 101 201 301 401
3 1-Mar-19 102 202 302 402
I want my to merge the 'a','b','c',and'd' columns with the '1'and '2' above them, so I'm doing the following to get my headers the way that I want:
import pandas as pd
import json
xls = pd.ExcelFile(r'C:Path_toExcel_Pandas_Connector_Test.xls')
df = pd.read_excel(xls, 'Sheet1', header=[1]) # uses the abcd row as column names
# I only want the most recent day of data so I do the following
json_str = df[df.Date == df['Date'].max()].to_json(orient='records',date_format='iso')
dat_data = json.loads(json_str)[0]
def clean_json():
global dat_data
dat_data['1a'] = dat_data.pop('a')
dat_data['1b'] = dat_data.pop('b')
dat_data['2c'] = dat_data.pop('c')
dat_data['2d'] = dat_data.pop('d')
clean_json()
print(json.dumps(dat_data,indent=4))
My desired output is:
"Date": "2019-03-01T00:00:00.000Z",
"1a": 102,
"1b": 202,
"2c": 302,
"2d": 402
This works as written, but is there a Pandas built-in that I could have used to do the same thing instead of the clean_json function?
python excel pandas
asked 59 mins ago
VirgilioVirgilio
62
New contributor
Virgilio is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I am reading an Excel file using Pandas and I feel like there has to be a better way to handle the way I create column names. This is something like the Excel file I'm reading:
1 2 # '1' is merged in the two cells above 'a'and 'b'
Date a b c d # likewise for '2'. As opposed to 'centered across selection'
1 1-Jan-19 100 200 300 400
2 1-Feb-19 101 201 301 401
3 1-Mar-19 102 202 302 402
I want my to merge the 'a','b','c',and'd' columns with the '1'and '2' above them, so I'm doing the following to get my headers the way that I want:
import pandas as pd
import json
xls = pd.ExcelFile(r'C:Path_toExcel_Pandas_Connector_Test.xls')
df = pd.read_excel(xls, 'Sheet1', header=[1]) # uses the abcd row as column names
# I only want the most recent day of data so I do the following
json_str = df[df.Date == df['Date'].max()].to_json(orient='records',date_format='iso')
dat_data = json.loads(json_str)[0]
def clean_json():
global dat_data
dat_data['1a'] = dat_data.pop('a')
dat_data['1b'] = dat_data.pop('b')
dat_data['2c'] = dat_data.pop('c')
dat_data['2d'] = dat_data.pop('d')
clean_json()
print(json.dumps(dat_data,indent=4))
My desired output is:
"Date": "2019-03-01T00:00:00.000Z",
"1a": 102,
"1b": 202,
"2c": 302,
"2d": 402
This works as written, but is there a Pandas built-in that I could have used to do the same thing instead of the clean_json function?
python excel pandas
python excel pandas
asked 59 mins ago
VirgilioVirgilio
62
New contributor
Virgilio is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 59 mins ago
VirgilioVirgilio
62
New contributor
Virgilio is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited 24 mins ago
Virgilio
asked 59 mins ago
VirgilioVirgilio
62
New contributor
Virgilio is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 59 mins ago
VirgilioVirgilio
62
asked 59 mins ago
VirgilioVirgilio
62
62
New contributor
Virgilio is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Virgilio is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Virgilio 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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