A tolerant version of df.loc
Search and replace values with df.loc without Exceptions due to dtype incompatibility. If the dtypes of 2 variables don't match, they will be converted until they match.
pip install a_pandas_ex_easy_loc
Some examples
import pandas as pd
df = pd.read_csv("https://github.com/pandas-dev/pandas/raw/main/doc/data/titanic.csv")
# df.loc[df.Ticket >20000]
from random import randrange
getrandomlist = lambda x: [
[[randrange(1, 100), randrange(1, 100)] * 1] * randrange(1, 10)
]
df["listtest"] = df.PassengerId.map(getrandomlist)
getrandomdict = lambda x: {
randrange(1, 100):randrange(1, 100) for _ in range(randrange(1, 10))
}
df["dicttest"] = df.PassengerId.map(getrandomdict)
from a_easy_loc import pd_add_easy_loc
pd_add_easy_loc()
df.shortloc_greater_replace('Pclass', 2,3000)
df.shortloc_equal('Pclass', 3)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3 Braund... male 22.00 1 0 A/5 21171 7.2500 NaN S [[[44,... {5: 8,...
2 3 1 3 Heikki... female 26.00 0 0 STON/O... 7.9250 NaN S [[[60,... {33: 3...
4 5 0 3 Allen,... male 35.00 0 0 373450 8.0500 NaN S [[[99,... {96: 1...
5 6 0 3 Moran,... male NaN 0 0 330877 8.4583 NaN Q [[[82,... {23: 1...
7 8 0 3 Palsso... male 2.00 3 1 349909 21.0750 NaN S [[[14,... {20: 8...
8 9 1 3 Johnso... female 27.00 0 2 347742 11.1333 NaN S [[[12,... {96: 5...
df.shortloc_equal('Ticket', 373450)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
4 5 0 3 Allen,... male 35.0 0 0 373450 8.05 NaN S [[[99,... {96: 1...
df.shortloc_greater('Pclass', 2)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3 Braund... male 22.00 1 0 A/5 21171 7.2500 NaN S [[[44,... {5: 8,...
2 3 1 3 Heikki... female 26.00 0 0 STON/O... 7.9250 NaN S [[[60,... {33: 3...
4 5 0 3 Allen,... male 35.00 0 0 373450 8.0500 NaN S [[[99,... {96: 1...
5 6 0 3 Moran,... male NaN 0 0 330877 8.4583 NaN Q [[[82,... {23: 1...
df.shortloc_greater('Ticket', 373450)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
16 17 0 3 Rice, ... male 2.0 4 1 382652 29.1250 NaN Q [[[17,... {46: 7...
50 51 0 3 Panula... male 7.0 4 1 3101295 39.6875 NaN S [[[30,... {64: 2...
68 69 1 3 Anders... female 17.0 4 2 3101281 7.9250 NaN S [[[4, ... {92: 3...
77 78 0 3 Moutal... male NaN 0 0 374746 8.0500 NaN S [[[65,... {47: 9...
85 86 1 3 Backst... female 33.0 3 0 3101278 15.8500 NaN S [[[55,... {5: 22...
df.shortloc_greater_or_equal('Age', 43)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
6 7 0 1 McCart... male 54.0 0 0 17463 51.8625 E46 S [[[47,... {22: 17}
11 12 1 1 Bonnel... female 58.0 0 0 113783 26.5500 C103 S [[[1, ... {35: 9}
15 16 1 2 Hewlet... female 55.0 0 0 248706 16.0000 NaN S [[[43,... {40: 6...
33 34 0 2 Wheado... male 66.0 0 0 C.A. 2... 10.5000 NaN S [[[6, ... {50: 28}
52 53 1 1 Harper... female 49.0 1 0 PC 17572 76.7292 D33 C [[[41,... {54: 6...
df.shortloc_greater_replace('Pclass', 2,3000)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3000 Braund... male 22.00 1 0 A/5 21171 7.2500 NaN S [[[65,... {76: 3...
1 2 1 1 Cuming... female 38.00 1 0 PC 17599 71.2833 C85 C [[[1, ... {55: 3...
2 3 1 3000 Heikki... female 26.00 0 0 STON/O... 7.9250 NaN S [[[56,... {7: 54...
3 4 1 1 Futrel... female 35.00 1 0 113803 53.1000 C123 S [[[91,... {51: 89}
4 5 0 3000 Allen,... male 35.00 0 0 373450 8.0500 NaN S [[[20,... {39: 5...
5 6 0 3000 Moran,... male NaN 0 0 330877 8.4583 NaN Q [[[60,... {63: 2...
6 7 0 1 McCart... male 54.00 0 0 17463 51.8625 E46 S [[[51,... {1: 90...
df.shortloc_greater_replace('Ticket', 5000, 888000)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3 Braund... male 22.00 1 0 A/5 21171 7.2500 NaN S [[[74,... {40: 3...
1 2 1 1 Cuming... female 38.00 1 0 PC 17599 71.2833 C85 C [[[67,... {1: 8}
2 3 1 3 Heikki... female 26.00 0 0 STON/O... 7.9250 NaN S [[[62,... {39: 79}
3 4 1 1 Futrel... female 35.00 1 0 888000 53.1000 C123 S [[[15,... {13: 2...
4 5 0 3 Allen,... male 35.00 0 0 888000 8.0500 NaN S [[[81,... {60: 90}
5 6 0 3 Moran,... male NaN 0 0 888000 8.4583 NaN Q [[[58,... {20: 4}
6 7 0 1 McCart... male 54.00 0 0 888000 51.8625 E46 S [[[28,... {21: 8...
7 8 0 3 Palsso... male 2.00 3 1 888000 21.0750 NaN S [[[25,... {53: 8...
8 9 1 3 Johnso... female 27.00 0 2 888000 11.1333 NaN S [[[47,... {19: 3...
df.shortloc_greater_replace('Cabin','C123', pd.NA)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3 Braund... male 22.00 1 0 A/5 21171 7.2500 NaN S [[[74,... {40: 3...
1 2 1 1 Cuming... female 38.00 1 0 PC 17599 71.2833 <NA> C [[[67,... {1: 8}
2 3 1 3 Heikki... female 26.00 0 0 STON/O... 7.9250 NaN S [[[62,... {39: 79}
3 4 1 1 Futrel... female 35.00 1 0 113803 53.1000 C123 S [[[15,... {13: 2...
4 5 0 3 Allen,... male 35.00 0 0 373450 8.0500 NaN S [[[81,... {60: 90}
5 6 0 3 Moran,... male NaN 0 0 330877 8.4583 NaN Q [[[58,... {20: 4}
6 7 0 1 McCart... male 54.00 0 0 17463 51.8625 <NA> S [[[28,... {21: 8...
7 8 0 3 Palsso... male 2.00 3 1 349909 21.0750 NaN S [[[25,... {53: 8...
df.shortloc_in_iter('listtest', 3)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
19 20 1 3 Masselmani, Mrs.... female NaN 0 0 2649 7.2250 NaN C [[[32, 3], [32, ... {98: 75, 69: 39,...
66 67 1 2 Nye, Mrs. (Eliza... female 29.0 0 0 C.A. 29395 10.5000 F33 S [[[3, 98], [3, 9... {60: 81}
92 93 0 1 Chaffee, Mr. Her... male 46.0 1 0 W.E.P. 5734 61.1750 E31 S [[[52, 3], [52, ... {80: 25}
106 107 1 3 Salkjelsvik, Mis... female 21.0 0 0 343120 7.6500 NaN S [[[85, 3], [85, ... {62: 49}
120 121 0 2 Hickman, Mr. Sta... male 21.0 2 0 S.O.C. 14879 73.5000 NaN S [[[40, 3], [40, ... {28: 85, 60: 72,...
129 130 0 3 Ekstrom, Mr. Johan male 45.0 0 0 347061 6.9750 NaN S [[[3, 76], [3, 7... {79: 2, 30: 18, ...
132 133 0 3 Robins, Mrs. Ale... female 47.0 1 0 A/5. 3337 14.5000 NaN S [[[3, 68], [3, 6... {69: 90, 1: 23, ...
184 185 1 3 Kink-Heilmann, M... female 4.0 0 2 315153 22.0250 NaN S [[[3, 88], [3, 8... {24: 74, 30: 11,...
df.shortloc_in_iter('listtest', [3,4,10])
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
19 20 1 3 Masselmani, Mrs.... female NaN 0 0 2649 7.2250 NaN C [[[32, 3], [32, ... {98: 75, 69: 39,...
22 23 1 3 McGowan, Miss. A... female 15.00 0 0 330923 8.0292 NaN Q [[[13, 4], [13, ... {56: 86, 30: 5, ...
27 28 0 1 Fortune, Mr. Cha... male 19.00 3 2 19950 263.0000 C23 C25 C27 S [[[4, 66], [4, 6... {58: 98, 32: 55,...
66 67 1 2 Nye, Mrs. (Eliza... female 29.00 0 0 C.A. 29395 10.5000 F33 S [[[3, 98], [3, 9... {60: 81}
74 75 1 3 Bing, Mr. Lee male 32.00 0 0 1601 56.4958 NaN S [[[14, 4], [14, ... {31: 31, 64: 38,...
84 85 1 2 Ilett, Miss. Bertha female 17.00 0 0 SO/C 14885 10.5000 NaN S [[[18, 10], [18,... {81: 64, 10: 80,...
df.shortloc_in_iter('dicttest', [3,4,10])
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
5 6 0 3 Moran, Mr. James male NaN 0 0 330877 8.4583 NaN Q [[[58, 72], [58, 72]]] {20: 4}
8 9 1 3 Johnson, Mrs. Oscar W (Eli... female 27.00 0 2 347742 11.1333 NaN S [[[47, 12], [47, 12]]] {19: 3, 60: 24, 9: 38}
df.shortloc_in_iter('dicttest', [3,4,10])
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
96 97 0 1 Goldschmidt, Mr. George B male 71.0 0 0 PC 17754 34.6542 A5 C [[[94, 4], [94, 4], [94, 4], [94, 4], [94, 4], [94, 4]]] {67: 92, 24: 19, 53: 40, 66: 53, 44: 81, 94: 10, 34: 63, 61: 45}
103 104 0 3 Johansson, Mr. Gustaf Joel male 33.0 0 0 7540 8.6542 NaN S [[[89, 10], [89, 10], [89, 10], [89, 10], [89, 10]]] {92: 23, 32: 17, 53: 3, 98: 94}
129 130 0 3 Ekstrom, Mr. Johan male 45.0 0 0 347061 6.9750 NaN S [[[3, 76], [3, 76], [3, 76], [3, 76], [3, 76], [3, 76], [3, 76]]] {79: 2, 30: 18, 63: 10, 62: 26, 91: 58, 11: 44, 8: 81, 6: 93, 97: 5}
df.shortloc_in_iter_replace('dicttest', [3,4,10], 15151515)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3 Braund, Mr. Owen Harris male 22.00 1 0 A/5 21171 7.2500 NaN S [[[74, 68], [74, 68], [74,... {40: 30, 93: 84, 24: 92, 7...
1 2 1 1 Cumings, Mrs. John Bradley... female 38.00 1 0 PC 17599 71.2833 C85 C [[[67, 64], [67, 64], [67,... {1: 8}
2 3 1 3 Heikkinen, Miss. Laina female 26.00 0 0 STON/O2. 3101282 7.9250 NaN S [[[62, 65], [62, 65], [62,... {39: 79}
3 4 1 1 Futrelle, Mrs. Jacques Hea... female 35.00 1 0 113803 53.1000 C123 S [[[15, 96], [15, 96], [15,... {13: 29, 65: 59, 99: 31}
4 5 0 3 Allen, Mr. William Henry male 35.00 0 0 373450 8.0500 NaN S [[[81, 13]]] {60: 90}
5 6 0 3 Moran, Mr. James male NaN 0 0 330877 8.4583 NaN Q [[[58, 72], [58, 72]]] 15151515
6 7 0 1 McCarthy, Mr. Timothy J male 54.00 0 0 17463 51.8625 E46 S [[[28, 98], [28, 98], [28,... {21: 8, 31: 42, 9: 40, 93:...
7 8 0 3 Palsson, Master. Gosta Leo... male 2.00 3 1 349909 21.0750 NaN S [[[25, 88], [25, 88], [25,... {53: 83, 49: 66, 57: 95, 4...
8 9 1 3 Johnson, Mrs. Oscar W (Eli... female 27.00 0 2 347742 11.1333 NaN S [[[47, 12], [47, 12]]] 15151515
df.shortloc_isin('Embarked', ['C', 'S'])
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3 Braund, Mr. Owen Harris male 22.00 1 0 A/5 21171 7.2500 NaN S [[[74, 68], [74, 68], [74,... {40: 30, 93: 84, 24: 92, 7...
1 2 1 1 Cumings, Mrs. John Bradley... female 38.00 1 0 PC 17599 71.2833 C85 C [[[67, 64], [67, 64], [67,... {1: 8}
2 3 1 3 Heikkinen, Miss. Laina female 26.00 0 0 STON/O2. 3101282 7.9250 NaN S [[[62, 65], [62, 65], [62,... {39: 79}
3 4 1 1 Futrelle, Mrs. Jacques Hea... female 35.00 1 0 113803 53.1000 C123 S [[[15, 96], [15, 96], [15,... {13: 29, 65: 59, 99: 31}
4 5 0 3 Allen, Mr. William Henry male 35.00 0 0 373450 8.0500 NaN S [[[81, 13]]] {60: 90}
6 7 0 1 McCarthy, Mr. Timothy J male 54.00 0 0 17463 51.8625 E46 S [[[28, 98], [28, 98], [28,... {21: 8, 31: 42, 9: 40, 93:...
7 8 0 3 Palsson, Master. Gosta Leo... male 2.00 3 1 349909 21.0750 NaN S [[[25, 88], [25, 88], [25,... {53: 83, 49: 66, 57: 95, 4...
8 9 1 3 Johnson, Mrs. Oscar W (Eli... female 27.00 0 2 347742 11.1333 NaN S [[[47, 12], [47, 12]]] {19: 3, 60: 24, 9: 38}
df.shortloc_isin_replace('Embarked', ['C', 'S'], 'CCCCCCCCCCCCCCCCCCCSSSSSSSSSSSSSSSSSSSSSSSSSSSSS')
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3 Braund... male 22.00 1 0 A/5 21171 7.2500 NaN CCCCCC... [[[74,... {40: 3...
1 2 1 1 Cuming... female 38.00 1 0 PC 17599 71.2833 C85 CCCCCC... [[[67,... {1: 8}
2 3 1 3 Heikki... female 26.00 0 0 STON/O... 7.9250 NaN CCCCCC... [[[62,... {39: 79}
3 4 1 1 Futrel... female 35.00 1 0 113803 53.1000 C123 CCCCCC... [[[15,... {13: 2...
4 5 0 3 Allen,... male 35.00 0 0 373450 8.0500 NaN CCCCCC... [[[81,... {60: 90}
5 6 0 3 Moran,... male NaN 0 0 330877 8.4583 NaN Q [[[58,... {20: 4}
df.shortloc_isna('Age')
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
5 6 0 3 Moran, Mr. James male NaN 0 0 330877 8.4583 NaN Q [[[25, 39], [25, 39]]] {97: 78, 85: 88, 42: 34}
17 18 1 2 Williams, Mr. Charles Eugene male NaN 0 0 244373 13.0000 NaN S [[[17, 6], [17, 6], [17, 6... {41: 6, 2: 82}
19 20 1 3 Masselmani, Mrs. Fatima female NaN 0 0 2649 7.2250 NaN C [[[11, 37], [11, 37], [11,... {43: 73, 50: 28, 38: 47, 4...
26 27 0 3 Emir, Mr. Farred Chehab male NaN 0 0 2631 7.2250 NaN C [[[48, 66], [48, 66], [48,... {33: 45, 82: 90}
28 29 1 3 O'Dwyer, Miss. Ellen "Nellie" female NaN 0 0 330959 7.8792 NaN Q [[[3, 53], [3, 53]]] {29: 90, 84: 86}
29 30 0 3 Todoroff, Mr. Lalio male NaN 0 0 349216 7.8958 NaN S [[[67, 3], [67, 3], [67, 3... {57: 49, 23: 71, 64: 45, 1...
31 32 1 1 Spencer, Mrs. William Augu... female NaN 1 0 PC 17569 146.5208 B78 C [[[88, 94], [88, 94], [88,... {4: 42, 98: 58, 94: 7, 39:...
df.shortloc_isna_replace('Age',16541)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3 Braund, Mr. Owen Harris male 22.00 1 0 A/5 21171 7.2500 NaN S [[[27, 71], [27, 71], [27,... {36: 67, 73: 54, 56: 48, 8...
1 2 1 1 Cumings, Mrs. John Bradley... female 38.00 1 0 PC 17599 71.2833 C85 C [[[31, 68], [31, 68], [31,... {9: 77}
2 3 1 3 Heikkinen, Miss. Laina female 26.00 0 0 STON/O2. 3101282 7.9250 NaN S [[[31, 23]]] {49: 6, 76: 22, 52: 18, 6:...
3 4 1 1 Futrelle, Mrs. Jacques Hea... female 35.00 1 0 113803 53.1000 C123 S [[[96, 48], [96, 48], [96,... {27: 90, 9: 38, 18: 94, 67...
4 5 0 3 Allen, Mr. William Henry male 35.00 0 0 373450 8.0500 NaN S [[[60, 84], [60, 84], [60,... {8: 61, 37: 4, 25: 43, 21:...
5 6 0 3 Moran, Mr. James male 16541.00 0 0 330877 8.4583 NaN Q [[[25, 39], [25, 39]]] {97: 78, 85: 88, 42: 34}
6 7 0 1 McCarthy, Mr. Timothy J male 54.00 0 0 17463 51.8625 E46 S [[[76, 5], [76, 5], [76, 5... {56: 51, 13: 24, 84: 24, 9...
df.shortloc_less('Ticket', 7534)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
19 20 1 3 Masselmani, Mrs. Fatima female NaN 0 0 2649 7.2250 NaN C [[[11, 37], [11, 37], [11,... {43: 73, 50: 28, 38: 47, 4...
26 27 0 3 Emir, Mr. Farred Chehab male NaN 0 0 2631 7.2250 NaN C [[[48, 66], [48, 66], [48,... {33: 45, 82: 90}
36 37 1 3 Mamee, Mr. Hanna male NaN 0 0 2677 7.2292 NaN C [[[84, 24], [84, 24], [84,... {39: 19, 88: 50, 23: 7, 53...
39 40 1 3 Nicola-Yarred, Miss. Jamila female 14.00 1 0 2651 11.2417 NaN C [[[20, 72], [20, 72], [20,... {72: 91, 81: 15, 89: 24, 9...
48 49 0 3 Samaan, Mr. Youssef male NaN 2 0 2662 21.6792 NaN C [[[79, 85], [79, 85], [79,... {35: 61}
53 54 1 2 Faunthorpe, Mrs. Lizzie (E... female 29.00 1 0 2926 26.0000 NaN S [[[62, 79], [62, 79]]] {36: 53, 38: 70, 6: 1, 89:...
57 58 0 3 Novel, Mr. Mansouer male 28.50 0 0 2697 7.2292 NaN C [[[86, 78], [86, 78]]] {28: 5, 49: 22}
60 61 0 3 Sirayanian, Mr. Orsen male 22.00 0 0 2669 7.2292 NaN C [[[24, 72]]] {74: 59, 16: 44, 30: 17, 5...
65 66 1 3 Moubarek, Master. Gerios male NaN 1 1 2661 15.2458 NaN C [[[56, 96], [56, 96], [56,... {5: 34, 59: 97, 78: 15, 76...
73 74 0 3 Chronopoulos, Mr. Apostolos male 26.00 1 0 2680 14.4542 NaN C [[[78, 24], [78, 24]]] {96: 26, 87: 73, 58: 49, 3...
74 75 1 3 Bing, Mr. Lee male 32.00 0 0 1601 56.4958 NaN S [[[86, 20], [86, 20], [86,... {84: 87, 18: 40, 17: 28, 7...
df.shortloc_less_replace('Age', 30, 'less 30')
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3 Braund, Mr. Owen Harris male less 30 1 0 A/5 21171 7.2500 NaN S [[[27, 71], [27, 71], [27,... {36: 67, 73: 54, 56: 48, 8...
1 2 1 1 Cumings, Mrs. John Bradley... female 38.0 1 0 PC 17599 71.2833 C85 C [[[31, 68], [31, 68], [31,... {9: 77}
2 3 1 3 Heikkinen, Miss. Laina female less 30 0 0 STON/O2. 3101282 7.9250 NaN S [[[31, 23]]] {49: 6, 76: 22, 52: 18, 6:...
3 4 1 1 Futrelle, Mrs. Jacques Hea... female 35.0 1 0 113803 53.1000 C123 S [[[96, 48], [96, 48], [96,... {27: 90, 9: 38, 18: 94, 67...
df.shortloc_less_or_equal_replace('Survived', 0, 'DEAD')
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 DEAD 3 Braund, Mr. Owen Harris male 22.00 1 0 A/5 21171 7.2500 NaN S [[[27, 71], [27, 71], [27,... {36: 67, 73: 54, 56: 48, 8...
1 2 1 1 Cumings, Mrs. John Bradley... female 38.00 1 0 PC 17599 71.2833 C85 C [[[31, 68], [31, 68], [31,... {9: 77}
2 3 1 3 Heikkinen, Miss. Laina female 26.00 0 0 STON/O2. 3101282 7.9250 NaN S [[[31, 23]]] {49: 6, 76: 22, 52: 18, 6:...
3 4 1 1 Futrelle, Mrs. Jacques Hea... female 35.00 1 0 113803 53.1000 C123 S [[[96, 48], [96, 48], [96,... {27: 90, 9: 38, 18: 94, 67...
4 5 DEAD 3 Allen, Mr. William Henry male 35.00 0 0 373450 8.0500 NaN S [[[60, 84], [60, 84], [60,... {8: 61, 37: 4, 25: 43, 21:...
5 6 DEAD 3 Moran, Mr. James male NaN 0 0 330877 8.4583 NaN Q [[[25, 39], [25, 39]]] {97: 78, 85: 88, 42: 34}
6 7 DEAD 1 McCarthy, Mr. Timothy J male 54.00 0 0 17463 51.8625 E46 S [[[76, 5], [76, 5], [76, 5... {56: 51, 13: 24, 84: 24, 9...
7 8 DEAD 3 Palsson, Master. Gosta Leo... male 2.00 3 1 349909 21.0750 NaN S [[[42, 52], [42, 52], [42,... {71: 69, 44: 14}
df.shortloc_not_equal_replace('Survived', 0, True)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3 Braund, Mr. Owen Harris male 22.00 1 0 A/5 21171 7.2500 NaN S [[[27, 71], [27, 71], [27,... {36: 67, 73: 54, 56: 48, 8...
1 2 True 1 Cumings, Mrs. John Bradley... female 38.00 1 0 PC 17599 71.2833 C85 C [[[31, 68], [31, 68], [31,... {9: 77}
2 3 True 3 Heikkinen, Miss. Laina female 26.00 0 0 STON/O2. 3101282 7.9250 NaN S [[[31, 23]]] {49: 6, 76: 22, 52: 18, 6:...
3 4 True 1 Futrelle, Mrs. Jacques Hea... female 35.00 1 0 113803 53.1000 C123 S [[[96, 48], [96, 48], [96,... {27: 90, 9: 38, 18: 94, 67...
4 5 0 3 Allen, Mr. William Henry male 35.00 0 0 373450 8.0500 NaN S [[[60, 84], [60, 84], [60,... {8: 61, 37: 4, 25: 43, 21:...
5 6 0 3 Moran, Mr. James male NaN 0 0 330877 8.4583 NaN Q [[[25, 39], [25, 39]]] {97: 78, 85: 88, 42: 34}
df.shortloc_not_in_iter('listtest', list(range(0,90)))
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
832 833 0 3 Saad, Mr. Amin male NaN 0 0 2671 7.2292 NaN C [[[95, 94], [95, 94], [95,... {82: 66, 84: 5}
484 485 1 1 Bishop, Mr. Dickinson H male 25.0 1 0 11967 91.0792 B49 C [[[97, 92], [97, 92], [97,... {20: 34, 2: 23, 98: 37, 1:...
581 582 1 1 Thayer, Mrs. John Borland ... female 39.0 1 1 17421 110.8833 C68 C [[[91, 90], [91, 90]]] {48: 98, 3: 98, 93: 4, 97:...
336 337 0 1 Pears, Mr. Thomas Clinton male 29.0 1 0 113776 66.6000 C2 S [[[90, 98], [90, 98]]] {6: 7}
116 117 0 3 Connors, Mr. Patrick male 70.5 0 0 370369 7.7500 NaN Q [[[92, 99], [92, 99], [92,... {60: 79, 75: 71, 28: 68, 5...
52 53 1 1 Harper, Mrs. Henry Sleeper... female 49.0 1 0 PC 17572 76.7292 D33 C [[[96, 94], [96, 94], [96,... {20: 53, 93: 11, 83: 79, 5...
439 440 0 2 Kvillner, Mr. Johan Henrik... male 31.0 0 0 C.A. 18723 10.5000 NaN S [[[95, 98], [95, 98], [95,... {58: 11, 89: 23, 22: 66, 1...
56 57 1 2 Rugg, Miss. Emily female 21.0 0 0 C.A. 31026 10.5000 NaN S [[[92, 92], [92, 92], [92,... {45: 1, 37: 98}
df.shortloc_not_in_iter_replace('listtest', list(range(0,20)), 27)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3 Braund, Mr. Owen Harris male 22.00 1 0 A/5 21171 7.2500 NaN S 27 {36: 67, 73: 54, 56: 48, 8...
1 2 1 1 Cumings, Mrs. John Bradley... female 38.00 1 0 PC 17599 71.2833 C85 C 27 {9: 77}
2 3 1 3 Heikkinen, Miss. Laina female 26.00 0 0 STON/O2. 3101282 7.9250 NaN S 27 {49: 6, 76: 22, 52: 18, 6:...
3 4 1 1 Futrelle, Mrs. Jacques Hea... female 35.00 1 0 113803 53.1000 C123 S 27 {27: 90, 9: 38, 18: 94, 67...
4 5 0 3 Allen, Mr. William Henry male 35.00 0 0 373450 8.0500 NaN S 27 {8: 61, 37: 4, 25: 43, 21:...
5 6 0 3 Moran, Mr. James male NaN 0 0 330877 8.4583 NaN Q 27 {97: 78, 85: 88, 42: 34}
6 7 0 1 McCarthy, Mr. Timothy J male 54.00 0 0 17463 51.8625 E46 S [[[76, 5], [76, 5], [76, 5... {56: 51, 13: 24, 84: 24, 9...
df.shortloc_regex('Fare', r'^\d?7\.').to_string(max_colwidth=30)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3 Braund, Mr. Owen Harris male 22.0 1 0 A/5 21171 7.2500 NaN S [[[27, 71], [27, 71], [27,... {36: 67, 73: 54, 56: 48, 8...
2 3 1 3 Heikkinen, Miss. Laina female 26.0 0 0 STON/O2. 3101282 7.9250 NaN S [[[31, 23]]] {49: 6, 76: 22, 52: 18, 6:...
14 15 0 3 Vestrom, Miss. Hulda Amand... female 14.0 0 0 350406 7.8542 NaN S [[[40, 57], [40, 57], [40,... {54: 39, 8: 35, 76: 84, 20...
19 20 1 3 Masselmani, Mrs. Fatima female NaN 0 0 2649 7.2250 NaN C [[[11, 37], [11, 37], [11,... {43: 73, 50: 28, 38: 47, 4...
26 27 0 3 Emir, Mr. Farred Chehab male NaN 0 0 2631 7.2250 NaN C [[[48, 66], [48, 66], [48,... {33: 45, 82: 90}
28 29 1 3 O'Dwyer, Miss. Ellen "Nellie" female NaN 0 0 330959 7.8792 NaN Q [[[3, 53], [3, 53]]] {29: 90, 84: 86}
29 30 0 3 Todoroff, Mr. Lalio male NaN 0 0 349216 7.8958 NaN S [[[67, 3], [67, 3], [67, 3... {57: 49, 23: 71, 64: 45, 1...
30 31 0 1 Uruchurtu, Don. Manuel E male 40.0 0 0 PC 17601 27.7208 NaN C [[[91, 32], [91, 32], [91,... {1: 29, 54: 93, 96: 7}
df.shortloc_not_regex('Fare', r'^\d?7\.').to_string(max_colwidth=30)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
1 2 1 1 Cumings, Mrs. John Bradley... female 38.00 1 0 PC 17599 71.2833 C85 C [[[31, 68], [31, 68], [31,... {9: 77}
3 4 1 1 Futrelle, Mrs. Jacques Hea... female 35.00 1 0 113803 53.1000 C123 S [[[96, 48], [96, 48], [96,... {27: 90, 9: 38, 18: 94, 67...
4 5 0 3 Allen, Mr. William Henry male 35.00 0 0 373450 8.0500 NaN S [[[60, 84], [60, 84], [60,... {8: 61, 37: 4, 25: 43, 21:...
5 6 0 3 Moran, Mr. James male NaN 0 0 330877 8.4583 NaN Q [[[25, 39], [25, 39]]] {97: 78, 85: 88, 42: 34}
6 7 0 1 McCarthy, Mr. Timothy J male 54.00 0 0 17463 51.8625 E46 S [[[76, 5], [76, 5], [76, 5... {56: 51, 13: 24, 84: 24, 9...
7 8 0 3 Palsson, Master. Gosta Leo... male 2.00 3 1 349909 21.0750 NaN S [[[42, 52], [42, 52], [42,... {71: 69, 44: 14}
8 9 1 3 Johnson, Mrs. Oscar W (Eli... female 27.00 0 2 347742 11.1333 NaN S [[[92, 21], [92, 21], [92,... {61: 17, 72: 44, 81: 74, 3...
9 10 1 2 Nasser, Mrs. Nicholas (Ade... female 14.00 1 0 237736 30.0708 NaN C [[[88, 97], [88, 97], [88,... {69: 43}
df.shortloc_str('Pclass', r'3').to_string(max_colwidth=30)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3 Braund, Mr. Owen Harris male 22.00 1 0 A/5 21171 7.2500 NaN S [[[27, 71], [27, 71], [27,... {36: 67, 73: 54, 56: 48, 8...
2 3 1 3 Heikkinen, Miss. Laina female 26.00 0 0 STON/O2. 3101282 7.9250 NaN S [[[31, 23]]] {49: 6, 76: 22, 52: 18, 6:...
4 5 0 3 Allen, Mr. William Henry male 35.00 0 0 373450 8.0500 NaN S [[[60, 84], [60, 84], [60,... {8: 61, 37: 4, 25: 43, 21:...
5 6 0 3 Moran, Mr. James male NaN 0 0 330877 8.4583 NaN Q [[[25, 39], [25, 39]]] {97: 78, 85: 88, 42: 34}
7 8 0 3 Palsson, Master. Gosta Leo... male 2.00 3 1 349909 21.0750 NaN S [[[42, 52], [42, 52], [42,... {71: 69, 44: 14}
8 9 1 3 Johnson, Mrs. Oscar W (Eli... female 27.00 0 2 347742 11.1333 NaN S [[[92, 21], [92, 21], [92,... {61: 17, 72: 44, 81: 74, 3...
10 11 1 3 Sandstrom, Miss. Marguerit... female 4.00 1 1 PP 9549 16.7000 G6 S [[[28, 63], [28, 63], [28,... {12: 80, 63: 96, 79: 99, 5...
12 13 0 3 Saundercock, Mr. William H... male 20.00 0 0 A/5. 2151 8.0500 NaN S [[[34, 91], [34, 91], [34,... {42: 68, 46: 90, 66: 96, 3...
13 14 0 3 Andersson, Mr. Anders Johan male 39.00 1 5 347082 31.2750 NaN S [[[3, 47], [3, 47], [3, 47... {94: 60, 73: 33, 59: 32, 3...
14 15 0 3 Vestrom, Miss. Hulda Amand... female 14.00 0 0 350406 7.8542 NaN S [[[40, 57], [40, 57], [40,... {54: 39, 8: 35, 76: 84, 20...
16 17 0 3 Rice, Master. Eugene male 2.00 4 1 382652 29.1250 NaN Q [[[24, 8], [24, 8], [24, 8... {20: 91, 56: 55, 11: 16, 3...
df.shortloc_str_replace('Pclass', r'3',4).to_string(max_colwidth=30)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 4 Braund, Mr. Owen Harris male 22.00 1 0 A/5 21171 7.2500 NaN S [[[27, 71], [27, 71], [27,... {36: 67, 73: 54, 56: 48, 8...
1 2 1 1 Cumings, Mrs. John Bradley... female 38.00 1 0 PC 17599 71.2833 C85 C [[[31, 68], [31, 68], [31,... {9: 77}
2 3 1 4 Heikkinen, Miss. Laina female 26.00 0 0 STON/O2. 3101282 7.9250 NaN S [[[31, 23]]] {49: 6, 76: 22, 52: 18, 6:...
3 4 1 1 Futrelle, Mrs. Jacques Hea... female 35.00 1 0 113803 53.1000 C123 S [[[96, 48], [96, 48], [96,... {27: 90, 9: 38, 18: 94, 67...
4 5 0 4 Allen, Mr. William Henry male 35.00 0 0 373450 8.0500 NaN S [[[60, 84], [60, 84], [60,... {8: 61, 37: 4, 25: 43, 21:...
5 6 0 4 Moran, Mr. James male NaN 0 0 330877 8.4583 NaN Q [[[25, 39], [25, 39]]] {97: 78, 85: 88, 42: 34}
6 7 0 1 McCarthy, Mr. Timothy J male 54.00 0 0 17463 51.8625 E46 S [[[76, 5], [76, 5], [76, 5... {56: 51, 13: 24, 84: 24, 9...
7 8 0 4 Palsson, Master. Gosta Leo... male 2.00 3 1 349909 21.0750 NaN S [[[42, 52], [42, 52], [42,... {71: 69, 44: 14}
8 9 1 4 Johnson, Mrs. Oscar W (Eli... female 27.00 0 2 347742 11.1333 NaN S [[[92, 21], [92, 21], [92,... {61: 17, 72: 44, 81: 74, 3...
9 10 1 2 Nasser, Mrs. Nicholas (Ade... female 14.00 1 0 237736 30.0708 NaN C [[[88, 97], [88, 97], [88,... {69: 43}
10 11 1 4 Sandstrom, Miss. Marguerit... female 4.00 1 1 PP 9549 16.7000 G6 S [[[28, 63], [28, 63], [28,... {12: 80, 63: 96, 79: 99, 5...
df.loc_positive_and(
("Pclass", "==", 3),
("Sex", "!=", "male"),
("Age", ">=", 1),
("Pclass", ">=", 3),
("listtest", "in_iter", [11, 22, 33, 44, 55, 66, 77, 88, 99]),
("Sex", "in", ["female", "male"]),
("Name", "re", r"Miss\."),
("Ticket", ">", 5000),
("Embarked", "str", "S"),
)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
24 25 0 3 Palsson, Miss. Torborg Danira female 8.0 3 1 349909 21.0750 NaN S [[[44, 33], [44, 33], [44,... {98: 85, 8: 23, 21: 77, 85...
141 142 1 3 Nysten, Miss. Anna Sofia female 22.0 0 0 347081 7.7500 NaN S [[[44, 30]]] {25: 15, 24: 14, 16: 26, 5...
192 193 1 3 Andersen-Jensen, Miss. Car... female 19.0 1 0 350046 7.8542 NaN S [[[39, 55], [39, 55], [39,... {1: 44, 16: 59, 80: 13, 81...
634 635 0 3 Skoog, Miss. Mabel female 9.0 3 2 347088 27.9000 NaN S [[[11, 22]]] {40: 7}
df.loc_positive_and(('Ticket','==', 373450), ('Pclass','==', 3))
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
4 5 0 3 Allen, Mr. William Henry male 35.0 0 0 373450 8.05 NaN S [[[60, 84], [60, 84], [60,... {8: 61, 37: 4, 25: 43, 21:...
df.loc_positive_or(('Ticket','==', 373450), ('Pclass','==', 3))
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
0 1 0 3 Braund, Mr. Owen Harris male 22.00 1 0 A/5 21171 7.2500 NaN S [[[27, 71], [27, 71], [27,... {36: 67, 73: 54, 56: 48, 8...
2 3 1 3 Heikkinen, Miss. Laina female 26.00 0 0 STON/O2. 3101282 7.9250 NaN S [[[31, 23]]] {49: 6, 76: 22, 52: 18, 6:...
4 5 0 3 Allen, Mr. William Henry male 35.00 0 0 373450 8.0500 NaN S [[[60, 84], [60, 84], [60,... {8: 61, 37: 4, 25: 43, 21:...
5 6 0 3 Moran, Mr. James male NaN 0 0 330877 8.4583 NaN Q [[[25, 39], [25, 39]]] {97: 78, 85: 88, 42: 34}
7 8 0 3 Palsson, Master. Gosta Leo... male 2.00 3 1 349909 21.0750 NaN S [[[42, 52], [42, 52], [42,... {71: 69, 44: 14}
df.loc_positive_and(('Age','>=', 13), ('Age','<=', 19))
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
9 10 1 2 Nasser, Mrs. Nicholas (Ade... female 14.0 1 0 237736 30.0708 NaN C [[[88, 97], [88, 97], [88,... {69: 43}
14 15 0 3 Vestrom, Miss. Hulda Amand... female 14.0 0 0 350406 7.8542 NaN S [[[40, 57], [40, 57], [40,... {54: 39, 8: 35, 76: 84, 20...
22 23 1 3 McGowan, Miss. Anna "Annie" female 15.0 0 0 330923 8.0292 NaN Q [[[85, 85], [85, 85], [85,... {80: 2, 70: 5, 27: 24, 10:...
27 28 0 1 Fortune, Mr. Charles Alexa... male 19.0 3 2 19950 263.0000 C23 C25 C27 S [[[7, 96], [7, 96], [7, 96... {60: 4, 22: 96, 55: 28, 97...
38 39 0 3 Vander Planke, Miss. Augus... female 18.0 2 0 345764 18.0000 NaN S [[[82, 50], [82, 50], [82,... {70: 41, 90: 86, 46: 95, 3...
39 40 1 3 Nicola-Yarred, Miss. Jamila female 14.0 1 0 2651 11.2417 NaN C [[[20, 72], [20, 72], [20,... {72: 91, 81: 15, 89: 24, 9...
44 45 1 3 Devaney, Miss. Margaret Delia female 19.0 0 0 330958 7.8792 NaN Q [[[97, 1], [97, 1], [97, 1... {89: 44, 58: 86, 48: 54, 9...
49 50 0 3 Arnold-Franchi, Mrs. Josef... female 18.0 1 0 349237 17.8000 NaN S [[[64, 68], [64, 68]]] {67: 59, 96: 34, 8: 64, 45...
67 68 0 3 Crease, Mr. Ernest James male 19.0 0 0 S.P. 3464 8.1583 NaN S [[[30, 77], [30, 77], [30,... {37: 56, 52: 5, 80: 12, 86...
df.loc_positive_and(('Ticket','!=', 373450), ('Pclass','!=', 3))
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
1 2 1 1 Cumings, Mrs. John Bradley... female 38.00 1 0 PC 17599 71.2833 C85 C [[[31, 68], [31, 68], [31,... {9: 77}
3 4 1 1 Futrelle, Mrs. Jacques Hea... female 35.00 1 0 113803 53.1000 C123 S [[[96, 48], [96, 48], [96,... {27: 90, 9: 38, 18: 94, 67...
6 7 0 1 McCarthy, Mr. Timothy J male 54.00 0 0 17463 51.8625 E46 S [[[76, 5], [76, 5], [76, 5... {56: 51, 13: 24, 84: 24, 9...
9 10 1 2 Nasser, Mrs. Nicholas (Ade... female 14.00 1 0 237736 30.0708 NaN C [[[88, 97], [88, 97], [88,... {69: 43}
11 12 1 1 Bonnell, Miss. Elizabeth female 58.00 0 0 113783 26.5500 C103 S [[[66, 84], [66, 84]]] {87: 7, 75: 62, 84: 22, 94...
15 16 1 2 Hewlett, Mrs. (Mary D King... female 55.00 0 0 248706 16.0000 NaN S [[[93, 7], [93, 7], [93, 7... {17: 96, 7: 68, 74: 5, 97:...
df.loc_negative_and(('Age','>=', 13), ('Sex','str', 'female'))
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
386 387 0 3 Goodwin, Master. Sidney Le... male 1.00 5 2 CA 2144 46.9000 NaN S [[[32, 26], [32, 26], [32,... {42: 33, 97: 56, 33: 73, 7...
261 262 1 3 Asplund, Master. Edvin Roj... male 3.00 4 2 347077 31.3875 NaN S [[[40, 73], [40, 73], [40,... {7: 23, 93: 3, 18: 66, 96:...
7 8 0 3 Palsson, Master. Gosta Leo... male 2.00 3 1 349909 21.0750 NaN S [[[42, 52], [42, 52], [42,... {71: 69, 44: 14}
16 17 0 3 Rice, Master. Eugene male 2.00 4 1 382652 29.1250 NaN Q [[[24, 8], [24, 8], [24, 8... {20: 91, 56: 55, 11: 16, 3...
787 788 0 3 Rice, Master. George Hugh male 8.00 4 1 382652 29.1250 NaN Q [[[32, 90], [32, 90], [32,... {5: 17, 83: 1, 82: 16, 21:...
788 789 1 3 Dean, Master. Bertram Vere male 1.00 1 2 C.A. 2315 20.5750 NaN S [[[27, 72], [27, 72], [27,... {58: 65, 42: 92, 61: 72}
278 279 0 3 Rice, Master. Eric male 7.00 4 1 382652 29.1250 NaN Q [[[48, 59], [48, 59], [48,... {16: 64, 97: 83, 66: 91, 9...
df.shortloc_regex('Name', '^Ab').shortloc_not_equal('Sex', 'male').shortloc_equal('Age', 35)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
279 280 1 3 Abbott, Mrs. Stanton (Rosa... female 35.0 1 1 C.A. 2673 20.25 NaN S [[[93, 85], [93, 85], [93,... {37: 16, 68: 58, 42: 7, 20...
df.shortloc_in_iter('dicttest', 65).shortloc_not_in_iter('listtest', [77,65,80,83])
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
515 516 0 1 Walker, Mr. William Anderson male 47.0 0 0 36967 34.0208 D46 S [[[55, 13], [55, 13], [55,... {67: 25, 73: 76, 93: 74, 6...
772 773 0 2 Mack, Mrs. (Mary) female 57.0 0 0 S.O./P.P. 3 10.5000 E77 S [[[3, 67], [3, 67], [3, 67... {20: 62, 88: 78, 22: 65, 1...
518 519 1 2 Angle, Mrs. William A (Flo... female 36.0 1 0 226875 26.0000 NaN S [[[78, 94], [78, 94]]] {32: 53, 48: 66, 20: 5, 67...
10 11 1 3 Sandstrom, Miss. Marguerit... female 4.0 1 1 PP 9549 16.7000 G6 S [[[28, 63], [28, 63], [28,... {12: 80, 63: 96, 79: 99, 5...
275 276 1 1 Andrews, Miss. Kornelia Th... female 63.0 1 0 13502 77.9583 D7 S [[[84, 21]]] {31: 95, 27: 48, 89: 25, 6...
788 789 1 3 Dean, Master. Bertram Vere male 1.0 1 2 C.A. 2315 20.5750 NaN S [[[27, 72], [27, 72], [27,... {58: 65, 42: 92, 61: 72}
df.shortloc_not_isna("Cabin").shortloc_str("Cabin", "C").shortloc_not_regex(
"Cabin", "^.{4,}$"
)
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
1 2 1 1 Cumings, Mrs. John Bradley... female 38.0 1 0 PC 17599 71.2833 C85 C [[[31, 68], [31, 68], [31,... {9: 77}
269 270 1 1 Bissette, Miss. Amelia female 35.0 0 0 PC 17760 135.6333 C99 S [[[89, 54], [89, 54], [89,... {50: 9, 91: 60, 30: 67, 46...
527 528 0 1 Farthing, Mr. John male NaN 0 0 PC 17483 221.7792 C95 S [[[9, 72], [9, 72], [9, 72... {41: 24, 63: 10}
151 152 1 1 Pears, Mrs. Thomas (Edith ... female 22.0 1 0 113776 66.6000 C2 S [[[24, 98], [24, 98], [24,... {80: 92, 25: 89, 32: 82, 1...
412 413 1 1 Minahan, Miss. Daisy E female 33.0 1 0 19928 90.0000 C78 Q [[[2, 41]]] {57: 41}
544 545 0 1 Douglas, Mr. Walter Donald male 50.0 1 0 PC 17761 106.4250 C86 C [[[55, 21], [55, 21], [55,... {51: 49, 16: 20}
550 551 1 1 Thayer, Mr. John Borland Jr male 17.0 0 2 17421 110.8833 C70 C [[[37, 20], [37, 20], [37,... {17: 85, 49: 77}
430 431 1 1 Bjornstrom-Steffansson, Mr... male 28.0 0 0 110564 26.5500 C52 S [[[14, 61], [14, 61], [14,... {62: 40}
df.shortloc_in_iter('listtest',[99, 77]).shortloc_regex('listtest',r"7\b,\s*\b9"))
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked listtest dicttest
111 112 0 3 Zabour, Miss. Hileni female 14.5 1 0 2665 14.4542 NaN C [[[27, 99], [27, 99], [27,... {76: 81, 62: 60, 98: 43, 5...
#all methods can also be used against Series
#Two examples
df.Pclass.shortloc_regex('^2$')
Out[54]:
9 2
15 2
17 2
20 2
21 2
..
df.Pclass.shortloc_regex_replace('^3$',2000)
Out[56]:
0 2000
1 1
2 2000
3 1
4 2000
...
Metadata
Release files for a-pandas-ex-easy-loc 0.15
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| a_pandas_ex_easy_loc-0.15.tar.gz | 40.4 kB | Without provenance | Details for a_pandas_ex_easy_loc-0.15.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| a_pandas_ex_easy_loc-0.15-py3-none-any.whl | Python 3 | none | any | Details for a_pandas_ex_easy_loc-0.15-py3-none-any.whl |
Total release size: 65.6 kB
Release files / a_pandas_ex_easy_loc-0.15.tar.gz
| Download URL | a_pandas_ex_easy_loc-0.15.tar.gz |
|---|---|
| Size | 40.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
5869c75fc5d8511b80b6b458d13f6b6c1d99b05449ac16a7c5598c1e33076c39
|
|
BLAKE2b-256 checksum How to use checksums |
8f406a34808583f5e942dd94f590863a70d89a339ae92d6f171c8f533064a3ae
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.10
|
Release files / a_pandas_ex_easy_loc-0.15-py3-none-any.whl
| Download URL | a_pandas_ex_easy_loc-0.15-py3-none-any.whl |
|---|---|
| Size | 25.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
7f64b070b8aa8f36662088331e8020e8c9ade1e4aeeb16f704148acee1baddde
|
|
BLAKE2b-256 checksum How to use checksums |
76641de2e4cdd418172179028ceef40cc19d5faf194fbd0d6d918c92055f8767
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.10
|
Security for a-pandas-ex-easy-loc 0.15
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.