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manojpandey / curl_post_json.md
Created November 20, 2018 14:41 — forked from ungoldman/curl_post_json.md
post a file JSON file with curl

How do POST file with curl??

You can post a json file with curl like so:

curl -X POST -H "Content-Type: application/json" -d @FILENAME DESTINATION

so for example:

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manojpandey / The Technical Interview Cheat Sheet.md
Created October 24, 2016 11:01 — forked from tsiege/The Technical Interview Cheat Sheet.md
This is my technical interview cheat sheet. Feel free to fork it or do whatever you want with it. PLEASE let me know if there are any errors or if anything crucial is missing. I will add more links soon.

Studying for a Tech Interview Sucks, so Here's a Cheat Sheet to Help

This list is meant to be a both a quick guide and reference for further research into these topics. It's basically a summary of that comp sci course you never took or forgot about, so there's no way it can cover everything in depth. It also will be available as a gist on Github for everyone to edit and add to.

Data Structure Basics

###Array ####Definition:

  • Stores data elements based on an sequential, most commonly 0 based, index.
  • Based on tuples from set theory.
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manojpandey / devup_ama_notes_jalem_raj_rohit
Created October 24, 2016 11:00 — forked from sudhirkhanger/devup_ama_notes_jalem_raj_rohit
Notes from Jalem Raj Rohit AMA on devup.in
Competitions:-
https://www.kaggle.com/
https://www.hackerearth.com/
Books:-
Introduction to Algorithms By Thomas H Cormen
Pattern Recognition and Machine Learning By Christopher M. Bishop
Freakonomics By Steven D. Levitt and Stephen J. Dubner
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manojpandey / hello_world.md
Created October 24, 2016 10:59 — forked from lava/hello_world.md
Hello, world: Analyzing a program to death.

Hello, world!

Please explain in detail what will happen if the following program is executed:

#include <iostream>

int main() {
    std::cout << "Hello, world!" << std::endl;
}
#List unique values in a DataFrame column
pd.unique(df.column_name.ravel())
#Convert Series datatype to numeric, getting rid of any non-numeric values
df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)
#Grab DataFrame rows where column has certain values
valuelist = ['value1', 'value2', 'value3']
df = df[df.column.isin(value_list)]