317 lines
5.5 KiB
Plaintext
317 lines
5.5 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "8cc1c960",
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"metadata": {},
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"source": [
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"# Pandas, quick introduction"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "0f55dab1",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4b377c42",
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"metadata": {},
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"source": [
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"# Pandas introduces a tabular data structure, the DataFrame\n",
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"\n",
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"* Columns can be of any C-native type\n",
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"* Columns and rows have indices, i.e. labels that identify each column or row"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "ec75edbe",
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"metadata": {},
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"outputs": [],
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"source": [
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"df = pd.DataFrame(\n",
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" data = [\n",
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" ['Anthony', 28, 1.53], \n",
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" ['Maria', 31, 1.76], \n",
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" ['Emma', 26, 1.83], \n",
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" ['Philip', 41, 1.81], \n",
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" ['Bill', 27, None],\n",
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" ],\n",
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" columns = ['name', 'age', 'height'],\n",
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" index=['A484', 'C012', 'A123', 'B663', 'A377'],\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "37318480",
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"metadata": {},
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"outputs": [],
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"source": [
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"df"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "fe1c5739",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "dedad6f3",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"id": "e31f21c6",
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"metadata": {},
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"source": [
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"## DataFrame attributes"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4109f1eb",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "708f9bb5",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"id": "cb2f33b9",
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"metadata": {},
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"source": [
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"## Indexing rows and columns"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "19ef2738",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8f354ffc",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "94563f03",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"id": "43ab5233",
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"metadata": {},
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"source": [
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"## Examining a column"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f2cb544c",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "86388f86",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"id": "fc081b90",
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"metadata": {},
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"source": [
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"# Filtering"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "263ae06c",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "318da062",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"id": "a570023a",
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"metadata": {},
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"source": [
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"# Basic operations are by column (unlike NumPy)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7260d212",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "49b7057a",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f5a0f053",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7e1ffe32",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"id": "7cf9b5d7",
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"metadata": {},
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"source": [
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"# Operations on strings"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b78bc237",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0236069f",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "5761725b",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "ce3d54ad",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"id": "8c5584db",
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"metadata": {},
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"source": [
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"# Adding new columns"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f6e09176",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f9a552f0",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "2e354ace",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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