logo
down
shadow

Resetting Index in a Dataframe drops the Indexed column by 1 row


Resetting Index in a Dataframe drops the Indexed column by 1 row

By : Jainish Jariwala
Date : October 22 2020, 08:10 PM
I wish this help you Since this is a presentation issue, consider using to_string with index=False:
code :
df = pd.DataFrame({'col1': [1, 2, 3],
                   'col2': [4, 5, 6]})

print(df.to_string(index=False))

col1  col2
   1     4
   2     5
   3     6
df.index.name = None
df = pd.DataFrame({'col1': [1, 2, 3],
                   'col2': [4, 5, 6]})

df = df.set_index('col1').rename_axis(None)

print(df)

   col2
1     4
2     5
3     6


Share : facebook icon twitter icon
Pandas DataFrame Add column to index without resetting

Pandas DataFrame Add column to index without resetting


By : Randy M
Date : March 29 2020, 07:55 AM
I wish did fix the issue. how do I add 'd' to the index below without having to reset it first? , We added an append option to set_index. Try that.
The command is:
code :
df.set_index(['d'], append=True)
pandas DataFrame drops index when passing to kdb+ (using qPython API)

pandas DataFrame drops index when passing to kdb+ (using qPython API)


By : user3144363
Date : March 29 2020, 07:55 AM
will help you While serializing DataFrame objects the qPython checks for the presence of meta attribute. If the attribute is not present, DataFrame is serialized as q table and index columns are skipped in the process. If you want to preserve the index columns, you have to set the meta attribute and provide type hinting to enforce representation a q keyed table.
Please take a look at the modified sample:
code :
import pandas.io.data as web
import datetime
import numpy
import qpython.qconnection as qconnection # requires installation of qPython module from https://github.com/exxeleron/qPython

from qpython import MetaData
from qpython.qtype import QKEYED_TABLE


start = datetime.datetime(2010, 1, 1)
end = datetime.datetime(2015, 2, 6)
f=web.DataReader("F", 'yahoo', start, end) # download Ford stock data (ticker "F") from Yahoo Finance web service
f.ix[:5]  # explore first 5 rows of the DataFrame
# Out:
#             Open  High  Low  Close    Volume  Adj Close
#    Date
# 2010-01-04 10.17 10.28 10.05 10.28  60855800       9.43 
# 2010-01-05 10.45 11.24 10.40 10.96 215620200      10.05
# 2010-01-06 11.21 11.46 11.13 11.37 200070600      10.43
# 2010-01-07 11.46 11.69 11.32 11.66 130201700      10.69
# 2010-01-08 11.67 11.74 11.46 11.69 130463000      10.72

q = qconnection.QConnection(host = 'localhost', port = 5000, pandas = True) # define connection interface parameters. Assumes we have previously started q server on port 5000 with `q.exe -p 5000` command
q.open() # open connection
f.meta = MetaData(**{'qtype': QKEYED_TABLE}) # enforce to serialize DataFrame as keyed table
q('set', numpy.string_('yahoo'), f) # pass DataFrame to q table named `yahoo`
q('5#yahoo') # display top 5 rows from newly created table on q server 
# Out:
#              Open   High    Low  Close     Volume  Adj Close
# Date                                                         
# 2010-01-04  10.17  10.28  10.05  10.28   60855800       9.43
# 2010-01-05  10.45  11.24  10.40  10.96  215620200      10.05
# 2010-01-06  11.21  11.46  11.13  11.37  200070600      10.43
# 2010-01-07  11.46  11.69  11.32  11.66  130201700      10.69
# 2010-01-08  11.67  11.74  11.46  11.69  130463000      10.72
How to select rows from an indexed pandas DataFrame, using the second indexed column?

How to select rows from an indexed pandas DataFrame, using the second indexed column?


By : user3476978
Date : March 29 2020, 07:55 AM
fixed the issue. Will look into that further Here is a trivial pandas DataFrame, with a two-level index and a single value column: , You can do that like this:
code :
df.loc[(slice(None), ['b', 'e']), :]
idx = pd.IndexSlice
df.loc[idx[:, ['b', 'e']], :]
Appending a multi-indexed column to the index of a DataFrame

Appending a multi-indexed column to the index of a DataFrame


By : Tomasz Swiderski
Date : March 29 2020, 07:55 AM
I wish did fix the issue. The DataFrame.set_index method takes an append keyword argument, so you can simply do like this:
code :
df_new = df.set_index(("Y", "d"), append=True)
df_new = df.set_index([("Y", "d"), ("Y", "e")], append=True)
Applying dependent mathematical operation to column in multi-indexed dataframe based on far left index

Applying dependent mathematical operation to column in multi-indexed dataframe based on far left index


By : user3279509
Date : March 29 2020, 07:55 AM
Hope this helps A faster approach than groupby.apply would be to combine GroupBy.max and .div matching indexes on level=0
code :
df.div(df.groupby(level=0).max(), level=0)
df.Stats.div(df.Stats.groupby(level=0).max(), level=0)
                       Stats
Stephen Curry 2010  0.714286
              2011  0.857143
              2012  1.000000
Chris Paul    2010  0.600000
              2011  0.800000
              2012  1.000000
df = pd.concat([df]*1000)

%timeit df.div(df.groupby(level=0).max(), level=0)
100 loops, best of 3: 3.02 ms per loop

%timeit df.groupby(level=0).apply(lambda x: x/x.max())
1 loop, best of 3: 8.88 s per loop
Related Posts Related Posts :
  • Submitting login form with scrapy
  • How do i edit the favicon in the Browsable API in Django REST framework?
  • multiprocessing.Pool.map_async doesn't seem to... do anything at all?
  • Python Selenium: Stale Element Reference Exception Error
  • Datetime conversion - How to extract the inferred format?
  • Import YAML variables automatically?
  • How to create a powershell shortcut for my python file
  • Python's 'set' operator doesn't work with numpy.nan
  • Pass object fields and one2many fields on same method - Odoo v8
  • Select columns based on column name and location in Pandas
  • Standardizing timeseries in Pandas using interpolation
  • How many tweets can be collected?
  • how format specifier taking value while tuple list is passed
  • How to print a numpy array with data type?
  • Timeout child thread for python3
  • How can I regroup a dataframe and accumulate a colume's values?
  • Bulk Insert into SQL Server with Python not working
  • Removing last rows of each group based on condition in a pandas dataframe
  • Why the css file can not be found in Django template?
  • targeting center of mass - scipy / numpy
  • Foursquare - get tips from VENUE_ID
  • Unpack a dictionary to format
  • encoding special characters in python2
  • Replacing integers with NaN results in the entire column becoming float dtype
  • Python 3.6 - BeautifulSoup4, parse table AttributeError: ResultSet object has no attribute 'findAll'
  • Convert panda date list to python list of date strings
  • escape response from Scrapy to parse json
  • How to create a same dropdown menu for different labels?
  • Why are some python variables uppercase whereas others are lowercase?
  • Machine Learning, What are the common techniques for feature engineering and presenting the model?
  • Modify value of a Django form field during clean() and validate again
  • Heroku Django app can't start up -- 'No module named site'
  • Getting list of dates (excluding weekends)
  • Im trying to create the regular expression to include the text and not the href
  • Python file.readline(2) reads first 2 charectars
  • Groupby with handling empty bin in python
  • Modifying Gcode
  • calling a value in a dictionary within a dictionary (reading a json file)
  • Bouncing ball invalid syntax why is that?
  • Python making a counter
  • Python rstrip and split
  • What does the String mean in numpy.r_?
  • How to correctly extend variable __all__ in a __init__.py?
  • Python behaves weird with piped input
  • Python 3 two dimensional list comprehension
  • How to slice image by broadcasting slices? Error: 'only integer scalar arrays can be converted to a scalar index' in pyt
  • (Python Beginner) Need a start on classes
  • IndexError: At least one sheet must be visible
  • How to solve a system of linear equations over the nonnegative integers?
  • Pandas keep the most complete rows
  • "List index out of range" error in Python Memory Match game
  • Numpy: how to use argmax results to get the actual max?
  • Google Cloud Dataflow can't import 'google.cloud.datastore'
  • Calculate pandas DataFrame column by custom routine which accepts dictionary as input
  • Connect to a Class Method by it's method name holded into a var in a for loop in python
  • PyQt5 signals and threading.Timer
  • Replace 2 characters in a string in python
  • Passing command line arguments from a folder script to a file script
  • Understand the syntaxe X[Y == c] in Numpy
  • Optimize beginner python script about substring replacement
  • shadow
    Privacy Policy - Terms - Contact Us © voile276.org