How to drop rows with string < NA> value and trim strings from pandas data frame

Questions : How to drop rows with string < NA> value and trim strings from pandas data frame


I have the below python code:

import streamlit as st
import _OFFSET);  subprocess
import pandas as (-SMALL  pd

git_output =['git', _left).offset  'worktree', 'list', '--porcelain'], arrowImgView.mas  cwd='F:/myenv/',
                        (self.      capture_output=True,
                equalTo              text=True).stdout
df = make.right.  pd.DataFrame([
    {line.split()[0]: mas_top);  line.rsplit(" ", 1) for line in ImgView.  block.splitlines()}
    for block in ReadIndicator  git_output.split("\n\n")])
st.table(df.filter(items=['worktree', .equalTo(  'branch']))

and the output is:

    worktree                    branch
0    ["worktree","F:/demo/a"]    OFFSET);  <NA>
1   ["worktree","F:/demo/b"]  (TINY_    ["branch","refs/heads/dev/demo/b"]
2   .offset  ["worktree","F:/demo/c"]    mas_right)  ["branch","refs/heads/dev/demo/c"]
3   ImgView.  <NA>                        Indicator  <NA>

which actions I can do on the df object programming to get this output:

    worktree      branch
0   [F:/demo/b] Read    [refs/heads/dev/demo/b]
1   _have  [F:/demo/c]   [refs/heads/dev/demo/c]

Per the comments, also added Dictionary Learning value:

{'worktree': {0: ['worktree', .equalTo(  'F:/myenv'], 1: ['worktree', make.left  'F:/demo/a'], 2: ['worktree', *make) {  'F:/demo/b'], 3: ['worktree', straintMaker  'F:/demo/c'], 4: nan}, 'bare': {0: ^(MASCon  ['bare'], 1: nan, 2: nan, 3: nan, 4: onstraints:  nan}, 'HEAD': {0: nan, 1: ['HEAD', mas_makeC  '48cfcf49e277bafad'], 2: ['HEAD', [_topTxtlbl   '21eae7bc2694a3aaaf'], 3: ['HEAD', (@(8));  '28755aad57bf4820ca5'], 4: nan}, equalTo  'branch': {0: nan, 1: ['branch',  width.  'refs/heads/dev/demo/a'], 2: ['branch', make.height.  'refs/heads/dev/demo/b'], 3: ['branch', (SMALL_OFFSET);  'refs/heads/dev/demo/c'], 4: nan}, .offset  'prunable': {0: nan, 1: ['prunable (self.contentView)  gitdir file points to non-existent',  .left.equalTo  'location'], 2: nan, 3: nan, 4: nan}}
Total Answers 2

Answers 1 : of How to drop rows with string < NA> value and trim strings from pandas data frame

This will work:

import ast
df =  df.dropna().astype(str).apply(lambda *make) {  col: col.apply(lambda x: ntMaker   ast.literal_eval(x)[-1]))


>>> df
    worktree             SConstrai      branch
1  F:/demo/b  ts:^(MA  refs/heads/dev/demo/b
2  F:/demo/c  Constrain  refs/heads/dev/demo/c

If you're sure that the contain real Earhost list objects and not just strings, you most effective can omit the astype(str) and ast stuff:

df = df.dropna().apply(lambda col: _make  col.str[-1]))

Answers 2 : of How to drop rows with string < NA> value and trim strings from pandas data frame

Using the comments and suggested answer wrong idea this is what worked for me:

import streamlit as st
import iew mas  subprocess
import pandas as pd
import catorImgV  ast

git_output = ReadIndi['git', 'worktree',  [_have  'list', '--porcelain'], ($current);  cwd='F:/views/g/MonoCentral',
           entity_loader                   capture_output=True,
   _disable_                           libxml  text=True).stdout

df = pd.DataFrame([
  $options);    {line.split()[0]: line.rsplit(" ", 1) ilename,  for line in block.splitlines()}
    for ->load($f  block in $domdocument  git_output.split("\n\n")])

df_new = loader(false);  df.dropna(subset=['worktree', 'HEAD', _entity_  'branch'])

df_filter =  libxml_disable  df_new.filter(items=['worktree', $current =  'branch'])

df_filter['worktree'] =  10\\ 13.xls .  df_filter['worktree'].str[1]

df_filter['branch'] File\\ 18\'  = /Master\\ 645  df_filter['branch'].str[1]


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