From 7f78152b2c3f07c8cefa1f4f5923bf43eded7ef4 Mon Sep 17 00:00:00 2001 From: Saeed Esmaili Date: Thu, 19 Dec 2024 20:28:57 +0100 Subject: [PATCH 1/2] Fix "john" in aggregation examples in readme --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 53f90f1..5e0474c 100644 --- a/README.md +++ b/README.md @@ -137,7 +137,7 @@ output Find the Max value for a certain column in certain aggregated columns ```python -l = [{"name": "John", "age": "16"}, {"name": "Mike", "age": "19"}, {"name": "Sarah", "age": "21"},{"name":"Joh","age":"19"}] +l = [{"name": "John", "age": "16"}, {"name": "Mike", "age": "19"}, {"name": "Sarah", "age": "21"},{"name":"john","age":"19"}] from leopards import Max count = Max(l,"age",['name'],dtype=int) ``` @@ -150,7 +150,7 @@ output * If you don't pass the aggregation columns, the maximum will be found across dataset. * You can pass the datatype of the column to convert it on the fly while evaluating ```python -l = [{"name": "John", "age": "16"}, {"name": "Mike", "age": "19"}, {"name": "Sarah", "age": "21"},{"name":"Joh","age":"19"}] +l = [{"name": "John", "age": "16"}, {"name": "Mike", "age": "19"}, {"name": "Sarah", "age": "21"},{"name":"john","age":"19"}] from leopards import Max m = Max(l,"age",dtype=int) ``` @@ -165,7 +165,7 @@ output Find the Max value for a certain column in certain aggregated columns ```python -l = [{"name": "John", "age": "16"}, {"name": "Mike", "age": "19"}, {"name": "Sarah", "age": "21"},{"name":"Joh","age":"19"}] +l = [{"name": "John", "age": "16"}, {"name": "Mike", "age": "19"}, {"name": "Sarah", "age": "21"},{"name":"john","age":"19"}] from leopards import Min m = Min(l,"age",['name']) ``` @@ -202,4 +202,4 @@ Thanks for [Asma Tahir](https://github.com/tahirasma) for Pandas stats. ## Tutorials -* [Work on CSV Files with Leopards](https://dev.to/mkalioby/working-with-csv-by-leopards-5bmd) \ No newline at end of file +* [Work on CSV Files with Leopards](https://dev.to/mkalioby/working-with-csv-by-leopards-5bmd) From 6aaacb1f5b59637cf21f517aea34a398be37a560 Mon Sep 17 00:00:00 2001 From: Saeed Esmaili Date: Thu, 19 Dec 2024 20:32:05 +0100 Subject: [PATCH 2/2] Update README.md --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 5e0474c..7ff0171 100644 --- a/README.md +++ b/README.md @@ -137,7 +137,7 @@ output Find the Max value for a certain column in certain aggregated columns ```python -l = [{"name": "John", "age": "16"}, {"name": "Mike", "age": "19"}, {"name": "Sarah", "age": "21"},{"name":"john","age":"19"}] +l = [{"name": "John", "age": "16"}, {"name": "Mike", "age": "19"}, {"name": "Sarah", "age": "21"},{"name":"John","age":"19"}] from leopards import Max count = Max(l,"age",['name'],dtype=int) ``` @@ -150,7 +150,7 @@ output * If you don't pass the aggregation columns, the maximum will be found across dataset. * You can pass the datatype of the column to convert it on the fly while evaluating ```python -l = [{"name": "John", "age": "16"}, {"name": "Mike", "age": "19"}, {"name": "Sarah", "age": "21"},{"name":"john","age":"19"}] +l = [{"name": "John", "age": "16"}, {"name": "Mike", "age": "19"}, {"name": "Sarah", "age": "21"},{"name":"John","age":"19"}] from leopards import Max m = Max(l,"age",dtype=int) ``` @@ -165,7 +165,7 @@ output Find the Max value for a certain column in certain aggregated columns ```python -l = [{"name": "John", "age": "16"}, {"name": "Mike", "age": "19"}, {"name": "Sarah", "age": "21"},{"name":"john","age":"19"}] +l = [{"name": "John", "age": "16"}, {"name": "Mike", "age": "19"}, {"name": "Sarah", "age": "21"},{"name":"John","age":"19"}] from leopards import Min m = Min(l,"age",['name']) ```